2022-11-18 09:14:50 +01:00
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< meta name = "author" content = "Marc Gauch" / >
2022-12-02 14:03:44 +01:00
< meta name = "date" content = "2022-12-02" / >
2022-11-18 09:14:50 +01:00
< title > Quantitative Methods HS22< / title >
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i m p o r t a n t } . l a b e l { b o r d e r : 1 p x s o l i d # 0 0 0 } . t a b l e { b o r d e r - c o l l a p s e : c o l l a p s e ! i m p o r t a n t } . t a b l e t d , . t a b l e t h { b a c k g r o u n d - c o l o r : # f f f ! i m p o r t a n t } . t a b l e - b o r d e r e d t d , . t a b l e - b o r d e r e d t h { b o r d e r : 1 p x s o l i d # d d d ! i m p o r t a n t } } @ f o n t - f a c e { f o n t - f a m i l y : ' G l y p h i c o n s H a l f l i n g s ' ; s r c : u r l ( d a t a : a p p l i c a t i o n / v n d . m s - f o n t o b j e c t ; b a s e 6 4 , n 0 4 A A E F N A A A C A A I A B A A A A A A A B Q A A A A A A A A A B A J A B A A A E A E x Q A A A A A A A A A A I A A A A A A A A A A A E A A A A A A A A A J x J / L A A A A A A A A A A A A A A A A A A A A A A A A C g A R w B M A F k A U A B I A E k A Q w B P A E 4 A U w A g A E g A Y Q B s A G Y A b A B p A G 4 A Z w B z A A A A D g B S A G U A Z w B 1 A G w A Y Q B y A A A A e A B W A G U A c g B z A G k A b w B u A C A A M Q A u A D A A M A A 5 A D s A U A B T A C A A M A A w A D E A L g A w A D A A O Q A 7 A G g A b w B 0 A G M A b w B u A H Y A I A A x A C 4 A M A A u A D c A M A A 7 A G 0 A Y Q B r A G U A b w B 0 A G Y A L g B s A G k A Y g A y A C 4 A N Q A u A D U A O A A z A D I A O Q A A A D g A R w B M A F k A U A B I A E k A Q w B P A E 4 A U w A g A E g A Y Q B s A G Y A b A B p A G 4 A Z w B z A C A A U g B l A G c A d Q B s A G E A c g A A A A A A Q l N H U A A A A A A A A A A A A A A A A A A A A A A D A K n c A E 0 T A E 0 Z A E b u F M 3 p j M / S E d m j K H U b y o w 8 A T B E 4 0 I v W A 3 v T u 8 L i A B D Q + p e x w U M c m 1 S M n N r y c t Q S i I 1 K 5 Z n b O l X K m n V V 5 Y v R e 6 R n N M F N C O s 1 K N V p n 6 y Z h C J k R t V R N z E u f e I q 7 H g S r c x 4 S 8 h / v 4 v n r r K c 6 o C N x m S k 2 u K l Z Q H B i i 6 i K F o H 0 7 4 6 T h v k O 1 k J H l x j r k x s + L W O R a D Q B E t i Y J I R 5 I B 9 B i 1 U y L 4 R m r 0 B N i g N k M z l K Q m n o f B H v i q V z U x w d M b 3 N d C n 6 9 h y + p R Y V K G V S / 1 t n s q v 4 L L 7 w C C P Z Z A Z P T 4 a C S h H j H J V N u X b m M r Y 5 L e Q a G n v A k X l V r J g K R A U d F j r W E a h 9 X e b P e Q M j 7 K S 7 D I B A F t 8 y c g C 5 P L G U O H S E 3 E r G Z C i V i N L L 5 Z A R f y w n C o Z a K Q C u 6 N u F X 4 2 A E e K t K U G n r / C m 2 C y 8 t p F h B P M W 5 F x i 4 Q m 4 T k D W h 4 I W F D C l h U 2 h R W o s U W q c K L l g y X B + l S H a W a H i W l B A R 8 S e S g S P C Q x d V Q g z U i x W K S T r I Q E b U 9 4 v i D c t k v X + V S j J u U m V 8 L 4 C X S h I 1 1 e s n p 0 p j W N Z I y x K H S 4 w V Q 2 i m e 1 P 4 R n h v G w 0 a D N 1 O L A X G E R s B 7 b u F p F G G B A r e 4 Q E Q R 0 H O I O 5 o Y H 3 0 5 G + K s p T / F u p E G G a f C C w x S e 6 Z U a + 0 7 3 r X H n N d V X E 6 e W
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* Includes: core.js, widget.js, mouse.js, position.js, draggable.js, droppable.js, resizable.js, selectable.js, sortable.js, accordion.js, autocomplete.js, button.js, dialog.js, menu.js, progressbar.js, selectmenu.js, slider.js, spinner.js, tabs.js, tooltip.js, effect.js, effect-blind.js, effect-bounce.js, effect-clip.js, effect-drop.js, effect-explode.js, effect-fade.js, effect-fold.js, effect-highlight.js, effect-puff.js, effect-pulsate.js, effect-scale.js, effect-shake.js, effect-size.js, effect-slide.js, effect-transfer.js
* Copyright jQuery Foundation and other contributors; Licensed MIT */
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< style type = "text/css" >
.tocify {
width: 20%;
max-height: 90%;
overflow: auto;
margin-left: 2%;
position: fixed;
border: 1px solid #ccc;
border-radius: 6px;
}
.tocify ul, .tocify li {
list-style: none;
margin: 0;
padding: 0;
border: none;
line-height: 30px;
}
.tocify-header {
text-indent: 10px;
}
.tocify-subheader {
text-indent: 20px;
display: none;
}
.tocify-subheader li {
font-size: 12px;
}
.tocify-subheader .tocify-subheader {
text-indent: 30px;
}
.tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 40px;
}
.tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 50px;
}
.tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 60px;
}
.tocify .tocify-item > a, .tocify .nav-list .nav-header {
margin: 0px;
}
.tocify .tocify-item a, .tocify .list-group-item {
padding: 5px;
}
.tocify .nav-pills > li {
float: none;
}
< / style >
< script > / * j q u e r y T o c i f y - v 1 . 9 . 1 - 2 0 1 3 - 1 0 - 2 2
* http://www.gregfranko.com/jquery.tocify.js/
* Copyright (c) 2013 Greg Franko; Licensed MIT */
// Immediately-Invoked Function Expression (IIFE) [Ben Alman Blog Post](http://benalman.com/news/2010/11/immediately-invoked-function-expression/) that calls another IIFE that contains all of the plugin logic. I used this pattern so that anyone viewing this code would not have to scroll to the bottom of the page to view the local parameters that were passed to the main IIFE.
(function(tocify) {
// ECMAScript 5 Strict Mode: [John Resig Blog Post](http://ejohn.org/blog/ecmascript-5-strict-mode-json-and-more/)
"use strict";
// Calls the second IIFE and locally passes in the global jQuery, window, and document objects
tocify(window.jQuery, window, document);
}
// Locally passes in `jQuery`, the `window` object, the `document` object, and an `undefined` variable. The `jQuery`, `window` and `document` objects are passed in locally, to improve performance, since javascript first searches for a variable match within the local variables set before searching the global variables set. All of the global variables are also passed in locally to be minifier friendly. `undefined` can be passed in locally, because it is not a reserved word in JavaScript.
(function($, window, document, undefined) {
// ECMAScript 5 Strict Mode: [John Resig Blog Post](http://ejohn.org/blog/ecmascript-5-strict-mode-json-and-more/)
"use strict";
var tocClassName = "tocify",
tocClass = "." + tocClassName,
tocFocusClassName = "tocify-focus",
tocHoverClassName = "tocify-hover",
hideTocClassName = "tocify-hide",
hideTocClass = "." + hideTocClassName,
headerClassName = "tocify-header",
headerClass = "." + headerClassName,
subheaderClassName = "tocify-subheader",
subheaderClass = "." + subheaderClassName,
itemClassName = "tocify-item",
itemClass = "." + itemClassName,
extendPageClassName = "tocify-extend-page",
extendPageClass = "." + extendPageClassName;
// Calling the jQueryUI Widget Factory Method
$.widget("toc.tocify", {
//Plugin version
version: "1.9.1",
// These options will be used as defaults
options: {
// **context**: Accepts String: Any jQuery selector
// The container element that holds all of the elements used to generate the table of contents
context: "body",
// **ignoreSelector**: Accepts String: Any jQuery selector
// A selector to any element that would be matched by selectors that you wish to be ignored
ignoreSelector: null,
// **selectors**: Accepts an Array of Strings: Any jQuery selectors
// The element's used to generate the table of contents. The order is very important since it will determine the table of content's nesting structure
selectors: "h1, h2, h3",
// **showAndHide**: Accepts a boolean: true or false
// Used to determine if elements should be shown and hidden
showAndHide: true,
// **showEffect**: Accepts String: "none", "fadeIn", "show", or "slideDown"
// Used to display any of the table of contents nested items
showEffect: "slideDown",
// **showEffectSpeed**: Accepts Number (milliseconds) or String: "slow", "medium", or "fast"
// The time duration of the show animation
showEffectSpeed: "medium",
// **hideEffect**: Accepts String: "none", "fadeOut", "hide", or "slideUp"
// Used to hide any of the table of contents nested items
hideEffect: "slideUp",
// **hideEffectSpeed**: Accepts Number (milliseconds) or String: "slow", "medium", or "fast"
// The time duration of the hide animation
hideEffectSpeed: "medium",
// **smoothScroll**: Accepts a boolean: true or false
// Determines if a jQuery animation should be used to scroll to specific table of contents items on the page
smoothScroll: true,
// **smoothScrollSpeed**: Accepts Number (milliseconds) or String: "slow", "medium", or "fast"
// The time duration of the smoothScroll animation
smoothScrollSpeed: "medium",
// **scrollTo**: Accepts Number (pixels)
// The amount of space between the top of page and the selected table of contents item after the page has been scrolled
scrollTo: 0,
// **showAndHideOnScroll**: Accepts a boolean: true or false
// Determines if table of contents nested items should be shown and hidden while scrolling
showAndHideOnScroll: true,
// **highlightOnScroll**: Accepts a boolean: true or false
// Determines if table of contents nested items should be highlighted (set to a different color) while scrolling
highlightOnScroll: true,
// **highlightOffset**: Accepts a number
// The offset distance in pixels to trigger the next active table of contents item
highlightOffset: 40,
// **theme**: Accepts a string: "bootstrap", "jqueryui", or "none"
// Determines if Twitter Bootstrap, jQueryUI, or Tocify classes should be added to the table of contents
theme: "bootstrap",
// **extendPage**: Accepts a boolean: true or false
// If a user scrolls to the bottom of the page and the page is not tall enough to scroll to the last table of contents item, then the page height is increased
extendPage: true,
// **extendPageOffset**: Accepts a number: pixels
// How close to the bottom of the page a user must scroll before the page is extended
extendPageOffset: 100,
// **history**: Accepts a boolean: true or false
// Adds a hash to the page url to maintain history
history: true,
// **scrollHistory**: Accepts a boolean: true or false
// Adds a hash to the page url, to maintain history, when scrolling to a TOC item
scrollHistory: false,
// **hashGenerator**: How the hash value (the anchor segment of the URL, following the
// # character) will be generated.
//
// "compact" (default) - #CompressesEverythingTogether
// "pretty" - #looks-like-a-nice-url-and-is-easily-readable
// function(text, element){} - Your own hash generation function that accepts the text as an
// argument, and returns the hash value.
hashGenerator: "compact",
// **highlightDefault**: Accepts a boolean: true or false
// Set's the first TOC item as active if no other TOC item is active.
highlightDefault: true
},
// _Create
// -------
// Constructs the plugin. Only called once.
_create: function() {
var self = this;
self.extendPageScroll = true;
// Internal array that keeps track of all TOC items (Helps to recognize if there are duplicate TOC item strings)
self.items = [];
// Generates the HTML for the dynamic table of contents
self._generateToc();
// Adds CSS classes to the newly generated table of contents HTML
self._addCSSClasses();
self.webkit = (function() {
for (var prop in window) {
if (prop) {
if (prop.toLowerCase().indexOf("webkit") !== -1) {
return true;
}
}
}
return false;
}());
// Adds jQuery event handlers to the newly generated table of contents
self._setEventHandlers();
// Binding to the Window load event to make sure the correct scrollTop is calculated
$(window).on("load", function() {
// Sets the active TOC item
self._setActiveElement(true);
// Once all animations on the page are complete, this callback function will be called
$("html, body").promise().done(function() {
setTimeout(function() {
self.extendPageScroll = false;
}, 0);
});
});
},
// _generateToc
// ------------
// Generates the HTML for the dynamic table of contents
_generateToc: function() {
// _Local variables_
// Stores the plugin context in the self variable
var self = this,
// All of the HTML tags found within the context provided (i.e. body) that match the top level jQuery selector above
firstElem,
// Instantiated variable that will store the top level newly created unordered list DOM element
ul,
ignoreSelector = self.options.ignoreSelector;
// Determine the element to start the toc with
// get all the top level selectors
firstElem = [];
var selectors = this.options.selectors.replace(/ /g, "").split(",");
// find the first set that have at least one non-ignored element
for(var i = 0; i < selectors.length ; i + + ) {
var foundSelectors = $(this.options.context).find(selectors[i]);
for (var s = 0; s < foundSelectors.length ; s + + ) {
if (!$(foundSelectors[s]).is(ignoreSelector)) {
firstElem = foundSelectors;
break;
}
}
if (firstElem.length> 0)
break;
}
if (!firstElem.length) {
self.element.addClass(hideTocClassName);
return;
}
self.element.addClass(tocClassName);
// Loops through each top level selector
firstElem.each(function(index) {
//If the element matches the ignoreSelector then we skip it
if ($(this).is(ignoreSelector)) {
return;
}
// Creates an unordered list HTML element and adds a dynamic ID and standard class name
ul = $("< ul / > ", {
"id": headerClassName + index,
"class": headerClassName
}).
// Appends a top level list item HTML element to the previously created HTML header
append(self._nestElements($(this), index));
// Add the created unordered list element to the HTML element calling the plugin
self.element.append(ul);
// Finds all of the HTML tags between the header and subheader elements
$(this).nextUntil(this.nodeName.toLowerCase()).each(function() {
// If there are no nested subheader elemements
if ($(this).find(self.options.selectors).length === 0) {
// Loops through all of the subheader elements
$(this).filter(self.options.selectors).each(function() {
//If the element matches the ignoreSelector then we skip it
if ($(this).is(ignoreSelector)) {
return;
}
self._appendSubheaders.call(this, self, ul);
});
}
// If there are nested subheader elements
else {
// Loops through all of the subheader elements
$(this).find(self.options.selectors).each(function() {
//If the element matches the ignoreSelector then we skip it
if ($(this).is(ignoreSelector)) {
return;
}
self._appendSubheaders.call(this, self, ul);
});
}
});
});
},
_setActiveElement: function(pageload) {
var self = this,
hash = window.location.hash.substring(1),
elem = self.element.find('li[data-unique="' + hash + '"]');
if (hash.length) {
// Removes highlighting from all of the list item's
self.element.find("." + self.focusClass).removeClass(self.focusClass);
// Highlights the current list item that was clicked
elem.addClass(self.focusClass);
// Triggers the click event on the currently focused TOC item
elem.click();
} else {
// Removes highlighting from all of the list item's
self.element.find("." + self.focusClass).removeClass(self.focusClass);
if (!hash.length & & pageload & & self.options.highlightDefault) {
// Highlights the first TOC item if no other items are highlighted
self.element.find(itemClass).first().addClass(self.focusClass);
}
}
return self;
},
// _nestElements
// -------------
// Helps create the table of contents list by appending nested list items
_nestElements: function(self, index) {
var arr, item, hashValue;
arr = $.grep(this.items, function(item) {
return item === self.text();
});
// If there is already a duplicate TOC item
if (arr.length) {
// Adds the current TOC item text and index (for slight randomization) to the internal array
this.items.push(self.text() + index);
}
// If there not a duplicate TOC item
else {
// Adds the current TOC item text to the internal array
this.items.push(self.text());
}
hashValue = this._generateHashValue(arr, self, index);
// Appends a list item HTML element to the last unordered list HTML element found within the HTML element calling the plugin
item = $("< li / > ", {
// Sets a common class name to the list item
"class": itemClassName,
"data-unique": hashValue
});
if (this.options.theme !== "bootstrap3") {
item.append($("< a / > ", {
"html": self.html()
}));
} else {
item.html(self.html());
}
// Adds an HTML anchor tag before the currently traversed HTML element
self.before($("< div / > ", {
// Sets a name attribute on the anchor tag to the text of the currently traversed HTML element (also making sure that all whitespace is replaced with an underscore)
"name": hashValue,
"data-unique": hashValue
}));
return item;
},
// _generateHashValue
// ------------------
// Generates the hash value that will be used to refer to each item.
_generateHashValue: function(arr, self, index) {
var hashValue = "",
hashGeneratorOption = this.options.hashGenerator;
if (hashGeneratorOption === "pretty") {
// prettify the text
hashValue = self.text().toLowerCase().replace(/\s/g, "-");
// fix double hyphens
while (hashValue.indexOf("--") > -1) {
hashValue = hashValue.replace(/--/g, "-");
}
// fix colon-space instances
while (hashValue.indexOf(":-") > -1) {
hashValue = hashValue.replace(/:-/g, "-");
}
} else if (typeof hashGeneratorOption === "function") {
// call the function
hashValue = hashGeneratorOption(self.text(), self);
} else {
// compact - the default
hashValue = self.text().replace(/\s/g, "");
}
// add the index if we need to
if (arr.length) {
hashValue += "" + index;
}
// return the value
return hashValue;
},
// _appendElements
// ---------------
// Helps create the table of contents list by appending subheader elements
_appendSubheaders: function(self, ul) {
// The current element index
var index = $(this).index(self.options.selectors),
// Finds the previous header DOM element
previousHeader = $(self.options.selectors).eq(index - 1),
currentTagName = +$(this).prop("tagName").charAt(1),
previousTagName = +previousHeader.prop("tagName").charAt(1),
lastSubheader;
// If the current header DOM element is smaller than the previous header DOM element or the first subheader
if (currentTagName < previousTagName ) {
// Selects the last unordered list HTML found within the HTML element calling the plugin
self.element.find(subheaderClass + "[data-tag=" + currentTagName + "]").last().append(self._nestElements($(this), index));
}
// If the current header DOM element is the same type of header(eg. h4) as the previous header DOM element
else if (currentTagName === previousTagName) {
ul.find(itemClass).last().after(self._nestElements($(this), index));
} else {
// Selects the last unordered list HTML found within the HTML element calling the plugin
ul.find(itemClass).last().
// Appends an unorderedList HTML element to the dynamic `unorderedList` variable and sets a common class name
after($("< ul / > ", {
"class": subheaderClassName,
"data-tag": currentTagName
})).next(subheaderClass).
// Appends a list item HTML element to the last unordered list HTML element found within the HTML element calling the plugin
append(self._nestElements($(this), index));
}
},
// _setEventHandlers
// ----------------
// Adds jQuery event handlers to the newly generated table of contents
_setEventHandlers: function() {
// _Local variables_
// Stores the plugin context in the self variable
var self = this,
// Instantiates a new variable that will be used to hold a specific element's context
$self,
// Instantiates a new variable that will be used to determine the smoothScroll animation time duration
duration;
// Event delegation that looks for any clicks on list item elements inside of the HTML element calling the plugin
this.element.on("click.tocify", "li", function(event) {
if (self.options.history) {
window.location.hash = $(this).attr("data-unique");
}
// Removes highlighting from all of the list item's
self.element.find("." + self.focusClass).removeClass(self.focusClass);
// Highlights the current list item that was clicked
$(this).addClass(self.focusClass);
// If the showAndHide option is true
if (self.options.showAndHide) {
var elem = $('li[data-unique="' + $(this).attr("data-unique") + '"]');
self._triggerShow(elem);
}
self._scrollTo($(this));
});
// Mouseenter and Mouseleave event handlers for the list item's within the HTML element calling the plugin
this.element.find("li").on({
// Mouseenter event handler
"mouseenter.tocify": function() {
// Adds a hover CSS class to the current list item
$(this).addClass(self.hoverClass);
// Makes sure the cursor is set to the pointer icon
$(this).css("cursor", "pointer");
},
// Mouseleave event handler
"mouseleave.tocify": function() {
if (self.options.theme !== "bootstrap") {
// Removes the hover CSS class from the current list item
$(this).removeClass(self.hoverClass);
}
}
});
// only attach handler if needed (expensive in IE)
if (self.options.extendPage || self.options.highlightOnScroll || self.options.scrollHistory || self.options.showAndHideOnScroll) {
// Window scroll event handler
$(window).on("scroll.tocify", function() {
// Once all animations on the page are complete, this callback function will be called
$("html, body").promise().done(function() {
// Local variables
// Stores how far the user has scrolled
var winScrollTop = $(window).scrollTop(),
// Stores the height of the window
winHeight = $(window).height(),
// Stores the height of the document
docHeight = $(document).height(),
scrollHeight = $("body")[0].scrollHeight,
// Instantiates a variable that will be used to hold a selected HTML element
elem,
lastElem,
lastElemOffset,
currentElem;
if (self.options.extendPage) {
// If the user has scrolled to the bottom of the page and the last toc item is not focused
if ((self.webkit & & winScrollTop >= scrollHeight - winHeight - self.options.extendPageOffset) || (!self.webkit & & winHeight + winScrollTop > docHeight - self.options.extendPageOffset)) {
if (!$(extendPageClass).length) {
lastElem = $('div[data-unique="' + $(itemClass).last().attr("data-unique") + '"]');
if (!lastElem.length) return;
// Gets the top offset of the page header that is linked to the last toc item
lastElemOffset = lastElem.offset().top;
// Appends a div to the bottom of the page and sets the height to the difference of the window scrollTop and the last element's position top offset
$(self.options.context).append($("< div / > ", {
"class": extendPageClassName,
"height": Math.abs(lastElemOffset - winScrollTop) + "px",
"data-unique": extendPageClassName
}));
if (self.extendPageScroll) {
currentElem = self.element.find('li.' + self.focusClass);
self._scrollTo($('div[data-unique="' + currentElem.attr("data-unique") + '"]'));
}
}
}
}
// The zero timeout ensures the following code is run after the scroll events
setTimeout(function() {
// _Local variables_
// Stores the distance to the closest anchor
var closestAnchorDistance = null,
// Stores the index of the closest anchor
closestAnchorIdx = null,
// Keeps a reference to all anchors
anchors = $(self.options.context).find("div[data-unique]"),
anchorText;
// Determines the index of the closest anchor
anchors.each(function(idx) {
var distance = Math.abs(($(this).next().length ? $(this).next() : $(this)).offset().top - winScrollTop - self.options.highlightOffset);
if (closestAnchorDistance == null || distance < closestAnchorDistance ) {
closestAnchorDistance = distance;
closestAnchorIdx = idx;
} else {
return false;
}
});
anchorText = $(anchors[closestAnchorIdx]).attr("data-unique");
// Stores the list item HTML element that corresponds to the currently traversed anchor tag
elem = $('li[data-unique="' + anchorText + '"]');
// If the `highlightOnScroll` option is true and a next element is found
if (self.options.highlightOnScroll & & elem.length) {
// Removes highlighting from all of the list item's
self.element.find("." + self.focusClass).removeClass(self.focusClass);
// Highlights the corresponding list item
elem.addClass(self.focusClass);
}
if (self.options.scrollHistory) {
if (window.location.hash !== "#" + anchorText) {
window.location.replace("#" + anchorText);
}
}
// If the `showAndHideOnScroll` option is true
if (self.options.showAndHideOnScroll & & self.options.showAndHide) {
self._triggerShow(elem, true);
}
}, 0);
});
});
}
},
// Show
// ----
// Opens the current sub-header
show: function(elem, scroll) {
// Stores the plugin context in the `self` variable
var self = this,
element = elem;
// If the sub-header is not already visible
if (!elem.is(":visible")) {
// If the current element does not have any nested subheaders, is not a header, and its parent is not visible
if (!elem.find(subheaderClass).length & & !elem.parent().is(headerClass) & & !elem.parent().is(":visible")) {
// Sets the current element to all of the subheaders within the current header
elem = elem.parents(subheaderClass).add(elem);
}
// If the current element does not have any nested subheaders and is not a header
else if (!elem.children(subheaderClass).length & & !elem.parent().is(headerClass)) {
// Sets the current element to the closest subheader
elem = elem.closest(subheaderClass);
}
//Determines what jQuery effect to use
switch (self.options.showEffect) {
//Uses `no effect`
case "none":
elem.show();
break;
//Uses the jQuery `show` special effect
case "show":
elem.show(self.options.showEffectSpeed);
break;
//Uses the jQuery `slideDown` special effect
case "slideDown":
elem.slideDown(self.options.showEffectSpeed);
break;
//Uses the jQuery `fadeIn` special effect
case "fadeIn":
elem.fadeIn(self.options.showEffectSpeed);
break;
//If none of the above options were passed, then a `jQueryUI show effect` is expected
default:
elem.show();
break;
}
}
// If the current subheader parent element is a header
if (elem.parent().is(headerClass)) {
// Hides all non-active sub-headers
self.hide($(subheaderClass).not(elem));
}
// If the current subheader parent element is not a header
else {
// Hides all non-active sub-headers
self.hide($(subheaderClass).not(elem.closest(headerClass).find(subheaderClass).not(elem.siblings())));
}
// Maintains chainablity
return self;
},
// Hide
// ----
// Closes the current sub-header
hide: function(elem) {
// Stores the plugin context in the `self` variable
var self = this;
//Determines what jQuery effect to use
switch (self.options.hideEffect) {
// Uses `no effect`
case "none":
elem.hide();
break;
// Uses the jQuery `hide` special effect
case "hide":
elem.hide(self.options.hideEffectSpeed);
break;
// Uses the jQuery `slideUp` special effect
case "slideUp":
elem.slideUp(self.options.hideEffectSpeed);
break;
// Uses the jQuery `fadeOut` special effect
case "fadeOut":
elem.fadeOut(self.options.hideEffectSpeed);
break;
// If none of the above options were passed, then a `jqueryUI hide effect` is expected
default:
elem.hide();
break;
}
// Maintains chainablity
return self;
},
// _triggerShow
// ------------
// Determines what elements get shown on scroll and click
_triggerShow: function(elem, scroll) {
var self = this;
// If the current element's parent is a header element or the next element is a nested subheader element
if (elem.parent().is(headerClass) || elem.next().is(subheaderClass)) {
// Shows the next sub-header element
self.show(elem.next(subheaderClass), scroll);
}
// If the current element's parent is a subheader element
else if (elem.parent().is(subheaderClass)) {
// Shows the parent sub-header element
self.show(elem.parent(), scroll);
}
// Maintains chainability
return self;
},
// _addCSSClasses
// --------------
// Adds CSS classes to the newly generated table of contents HTML
_addCSSClasses: function() {
// If the user wants a jqueryUI theme
if (this.options.theme === "jqueryui") {
this.focusClass = "ui-state-default";
this.hoverClass = "ui-state-hover";
//Adds the default styling to the dropdown list
this.element.addClass("ui-widget").find(".toc-title").addClass("ui-widget-header").end().find("li").addClass("ui-widget-content");
}
// If the user wants a twitterBootstrap theme
else if (this.options.theme === "bootstrap") {
this.element.find(headerClass + "," + subheaderClass).addClass("nav nav-list");
this.focusClass = "active";
}
// If the user wants a twitterBootstrap theme
else if (this.options.theme === "bootstrap3") {
this.element.find(headerClass + "," + subheaderClass).addClass("list-group");
this.element.find(itemClass).addClass("list-group-item");
this.focusClass = "active";
}
// If a user does not want a prebuilt theme
else {
// Adds more neutral classes (instead of jqueryui)
this.focusClass = tocFocusClassName;
this.hoverClass = tocHoverClassName;
}
//Maintains chainability
return this;
},
// setOption
// ---------
// Sets a single Tocify option after the plugin is invoked
setOption: function() {
// Calls the jQueryUI Widget Factory setOption method
$.Widget.prototype._setOption.apply(this, arguments);
},
// setOptions
// ----------
// Sets a single or multiple Tocify options after the plugin is invoked
setOptions: function() {
// Calls the jQueryUI Widget Factory setOptions method
$.Widget.prototype._setOptions.apply(this, arguments);
},
// _scrollTo
// ---------
// Scrolls to a specific element
_scrollTo: function(elem) {
var self = this,
duration = self.options.smoothScroll || 0,
scrollTo = self.options.scrollTo,
currentDiv = $('div[data-unique="' + elem.attr("data-unique") + '"]');
if (!currentDiv.length) {
return self;
}
// Once all animations on the page are complete, this callback function will be called
$("html, body").promise().done(function() {
// Animates the html and body element scrolltops
$("html, body").animate({
// Sets the jQuery `scrollTop` to the top offset of the HTML div tag that matches the current list item's `data-unique` tag
"scrollTop": currentDiv.offset().top - ($.isFunction(scrollTo) ? scrollTo.call() : scrollTo) + "px"
}, {
// Sets the smoothScroll animation time duration to the smoothScrollSpeed option
"duration": duration
});
});
// Maintains chainability
return self;
}
});
})); //end of plugin
< / script >
< script >
/**
* jQuery Plugin: Sticky Tabs
*
* @author Aidan Lister < aidan @ php . net >
* adapted by Ruben Arslan to activate parent tabs too
* http://www.aidanlister.com/2014/03/persisting-the-tab-state-in-bootstrap/
*/
(function($) {
"use strict";
$.fn.rmarkdownStickyTabs = function() {
var context = this;
// Show the tab corresponding with the hash in the URL, or the first tab
var showStuffFromHash = function() {
var hash = window.location.hash;
var selector = hash ? 'a[href="' + hash + '"]' : 'li.active > a';
var $selector = $(selector, context);
if($selector.data('toggle') === "tab") {
$selector.tab('show');
// walk up the ancestors of this element, show any hidden tabs
$selector.parents('.section.tabset').each(function(i, elm) {
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< h1 class = "title toc-ignore" > Quantitative Methods HS22< / h1 >
< h4 class = "author" > Marc Gauch< / h4 >
2022-12-02 14:03:44 +01:00
< h4 class = "date" > 2022-12-02< / h4 >
2022-11-18 09:14:50 +01:00
< / div >
< div id = "preparation" class = "section level1" number = "1" >
< h1 > < span class = "header-section-number" > 1< / span > Preparation< / h1 >
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< pre class = "r" > < code > if (!require(tidyverse)) {
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install.packages(" tidyverse" )
library(tidyverse)
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}
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if (!require(e1071)) {
install.packages(" e1071" )
library(e1071)
2022-11-18 21:01:02 +01:00
}< / code > < / pre >
< / div >
< div id = "own-functions" class = "section level1" number = "2" >
< h1 > < span class = "header-section-number" > 2< / span > Own functions< / h1 >
< div id = "frequency-table-ordered-from-wish.com" class = "section level2" number = "2.1" >
< h2 > < span class = "header-section-number" > 2.1< / span > Frequency Table
ordered from wish.com< / h2 >
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< pre class = "r" > < code > freq < - function(data, rounded_digits = 2) {
# counts
total_count < - length(data)
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na_count < - length(data[is.na(data)])
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valid_count < - total_count - na_count
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frequency < - table(data)
p < - prop.table(frequency)
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valid_percent < - round(p * 100, digits = rounded_digits)
na_percent < - round(na_count / length(data) * 100, digits = rounded_digits)
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percent_raw < - frequency/total_count*100
percent < - round(percent_raw, digits = rounded_digits)
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cumulative_percent < - round(cumsum(p) * 100, digits = rounded_digits)
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freq_table < - cbind(frequency, percent, percent_raw, valid_percent, cumulative_percent)
2022-11-25 16:31:02 +01:00
2022-11-25 16:44:01 +01:00
valid_percent_sum < - round(sum(as.data.frame(freq_table)$percent_raw), digits = rounded_digits)
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Valid_Total < - c(valid_count, valid_percent_sum, 100, NaN)
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freq_table < - subset(freq_table, select = -c(percent_raw))
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NAs < - c(na_count, na_percent, NaN, NaN)
Total < - c(total_count, 100, NaN, NaN)
print(rbind(freq_table, Valid_Total, NAs, Total))
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}< / code > < / pre >
< p > < em > Source: < a href = "https://tellmi.psy.lmu.de/tutorials/deskriptive-statistiken-und-grafiken.html#haeufigkeiten-diskret" class = "uri" > https://tellmi.psy.lmu.de/tutorials/deskriptive-statistiken-und-grafiken.html#haeufigkeiten-diskret< / a >
and adapted< / em > < / p >
< / div >
< div id = "modus" class = "section level2" number = "2.2" >
< h2 > < span class = "header-section-number" > 2.2< / span > Modus< / h2 >
< pre class = "r" > < code > getmode < - function(v) {
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uniqv < - unique(v)
x < - tabulate(match(v, uniqv))
uniqv[which(x == max(x))]
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}< / code > < / pre >
< / div >
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< / div >
< div id = "load-data" class = "section level1" number = "3" >
< h1 > < span class = "header-section-number" > 3< / span > Load Data< / h1 >
< div id = "load-from-csv" class = "section level2" number = "3.1" >
< h2 > < span class = "header-section-number" > 3.1< / span > Load from CSV< / h2 >
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< pre class = "r" > < code > litdata < - read_csv(" DataLit_R.csv" , show_col_types = FALSE)
litdata < - as_tibble(litdata)< / code > < / pre >
< / div >
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< div id = "first-inspection-of-data" class = "section level2 tabset" number = "3.2" >
< h2 class = "tabset" > < span class = "header-section-number" > 3.2< / span > First
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inspection of data< / h2 >
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< div id = "summary" class = "section level3" number = "3.2.1" >
< h3 > < span class = "header-section-number" > 3.2.1< / span > Summary< / h3 >
2022-11-18 09:14:50 +01:00
< pre class = "r" > < code > summary(litdata)< / code > < / pre >
< pre > < code > ## id submitdate lastpage startlanguage
## Min. : 1 Length:313 Min. :-1.000 Length:313
## 1st Qu.: 81 Class :character 1st Qu.: 2.000 Class :character
## Median :162 Mode :character Median : 5.000 Mode :character
## Mean :163 Mean : 3.556
## 3rd Qu.:245 3rd Qu.: 5.000
## Max. :327 Max. : 5.000
## NA' s :108
## seed startdate datestamp W001
## Min. :5.647e+06 Length:313 Length:313 Length:313
## 1st Qu.:5.568e+08 Class :character Class :character Class :character
## Median :1.086e+09 Mode :character Mode :character Mode :character
## Mean :1.081e+09
## 3rd Qu.:1.637e+09
## Max. :2.147e+09
##
## W002 W003 W004 W005
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
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## W006 W007 W008 W009
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
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## K001 K002 K003 K004
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
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## K005 K006 K007 K008
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
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## K009 TK001_01 TK001_02 TK001_03
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
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## TK003_04 TK004_01 TK004_02 TK004_03
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## TK004_04 TK005_01 TK005_02 TK005_03
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## TK005_04 TK006_01 TK006_02 TK006_03
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## TK006_04 H001_001 H001_002 H001_003
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## H001_004 H001_005 H001_006 H001_007
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## H002 H003 H004 H004_other
## Length:313 Length:313 Length:313 Length:313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## H005 H005_other H006 H007
## Length:313 Mode:logical Min. :2012 Min. :1971
## Class :character NA' s:313 1st Qu.:2018 1st Qu.:1991
## Mode :character Median :2020 Median :1995
## Mean :2019 Mean :1993
## 3rd Qu.:2020 3rd Qu.:1998
## Max. :2021 Max. :2002
## NA' s :201 NA' s :207
## H008 R1
## Length:313 Length:313
## Class :character Class :character
## Mode :character Mode :character
##
##
##
## < / code > < / pre >
< / div >
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< div id = "glimpse" class = "section level3" number = "3.2.2" >
< h3 > < span class = "header-section-number" > 3.2.2< / span > Glimpse< / h3 >
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< pre class = "r" > < code > glimpse(litdata)< / code > < / pre >
< pre > < code > ## Rows: 313
## Columns: 66
## $ id < dbl> 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, …
## $ submitdate < chr> " 10/25/2021 11:07:44" , NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ lastpage < dbl> 5, NA, NA, 2, 2, NA, NA, NA, 2, 1, NA, NA, 5, NA, NA, NA…
## $ startlanguage < chr> " en" , " de" , " de" , " de" , " en" , " de" , " de" , " de" , " en" , " d…
## $ seed < dbl> 664891087, 334145431, 683903577, 2082427237, 438283320, …
## $ startdate < chr> " 10/25/2021 11:07:40" , " 10/25/2021 11:33:06" , " 10/25/202…
## $ datestamp < chr> " 10/25/2021 11:07:44" , " 10/25/2021 11:33:06" , " 10/25/202…
## $ W001 < chr> NA, NA, NA, " Stimme voll zu5" , " 3" , NA, NA, NA, " Stimme …
## $ W002 < chr> NA, NA, NA, " Stimme voll zu5" , " 3" , NA, NA, NA, " 4" , " 2" …
## $ W003 < chr> NA, NA, NA, " 4" , " 3" , NA, NA, NA, " 4" , " 4" , NA, NA, " Sti…
## $ W004 < chr> NA, NA, NA, " Stimme voll zu5" , " Stimme voll zu5" , NA, NA…
## $ W005 < chr> NA, NA, NA, " Stimme voll zu5" , " Stimme voll zu5" , NA, NA…
## $ W006 < chr> NA, NA, NA, " 4" , " 4" , NA, NA, NA, " 4" , " 4" , NA, NA, " 4" ,…
## $ W007 < chr> NA, NA, NA, " 4" , " Stimme voll zu5" , NA, NA, NA, " Stimme …
## $ W008 < chr> NA, NA, NA, " Stimme voll zu5" , " 4" , NA, NA, NA, " Stimme …
## $ W009 < chr> NA, NA, NA, " Stimme voll zu5" , " Stimme voll zu5" , NA, NA…
## $ K001 < chr> NA, NA, NA, " 4" , " 4" , NA, NA, NA, " 4" , NA, NA, NA, " 3" , …
## $ K002 < chr> NA, NA, NA, " 3" , " 3" , NA, NA, NA, " 4" , NA, NA, NA, " 4" , …
## $ K003 < chr> NA, NA, NA, " 3" , " Stimme voll zu5" , NA, NA, NA, " 3" , NA,…
## $ K004 < chr> NA, NA, NA, " 3" , " 4" , NA, NA, NA, " 4" , NA, NA, NA, " 3" , …
## $ K005 < chr> NA, NA, NA, " 4" , " 3" , NA, NA, NA, " 4" , NA, NA, NA, " 3" , …
## $ K006 < chr> NA, NA, NA, " 4" , " 4" , NA, NA, NA, " 4" , NA, NA, NA, " 4" , …
## $ K007 < chr> NA, NA, NA, " 4" , " 3" , NA, NA, NA, " 3" , NA, NA, NA, " 4" , …
## $ K008 < chr> NA, NA, NA, " 4" , " 3" , NA, NA, NA, " 4" , NA, NA, NA, " Stim…
## $ K009 < chr> NA, NA, NA, " 4" , " 2" , NA, NA, NA, " 4" , NA, NA, NA, " Stim…
## $ TK001_01 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ TK001_02 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK001_03 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK001_04 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ TK002_01 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ TK002_02 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK002_03 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK002_04 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ TK003_01 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 3" , NA,…
## $ TK003_02 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ TK003_03 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK003_04 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK004_01 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK004_02 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK004_03 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK004_04 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ TK005_01 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK005_02 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK005_03 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK005_04 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK006_01 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK006_02 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK006_03 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Stimme …
## $ TK006_04 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " 4" , NA,…
## $ H001_001 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Ja" , NA…
## $ H001_002 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Nicht G…
## $ H001_003 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Ja" , NA…
## $ H001_004 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Nicht G…
## $ H001_005 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Nicht G…
## $ H001_006 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Nicht G…
## $ H001_007 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Nicht G…
## $ H002 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Ja" , NA…
## $ H003 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Bibliot…
## $ H004 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Gesundh…
## $ H004_other < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ H005 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Bachelo…
## $ H005_other < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ H006 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ H007 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ H008 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Weiblic…
## $ R1 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Die Fra…< / code > < / pre >
< / div >
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< div id = "print" class = "section level3" number = "3.2.3" >
< h3 > < span class = "header-section-number" > 3.2.3< / span > Print< / h3 >
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< pre class = "r" > < code > print(litdata)< / code > < / pre >
< pre > < code > ## # A tibble: 313 ×
## id submit…¹ lastp…² start…³ seed start…⁴ dates…⁵ W001 W002 W003 W004
## < dbl> < chr> < dbl> < chr> < dbl> < chr> < chr> < chr> < chr> < chr> < chr>
## 1 1 10/25/2… 5 en 6.65e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 2 2 < NA> NA de 3.34e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 3 3 < NA> NA de 6.84e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 4 5 < NA> 2 de 2.08e9 10/25/… 10/25/… Stim… Stim… 4 Stim…
## 5 6 < NA> 2 en 4.38e8 10/25/… 10/25/… 3 3 3 Stim…
## 6 7 < NA> NA de 2.15e9 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 7 8 < NA> NA de 1.74e9 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 8 9 < NA> NA de 4.64e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 9 10 < NA> 2 en 1.09e9 10/25/… 10/25/… Stim… 4 4 4
## 10 11 < NA> 1 de 1.55e9 10/25/… 10/25/… 3 2 4 4
## # … with 303 more rows, 55 more variables: W005 < chr> , W006 < chr> , W007 < chr> ,
## # W008 < chr> , W009 < chr> , K001 < chr> , K002 < chr> , K003 < chr> , K004 < chr> ,
## # K005 < chr> , K006 < chr> , K007 < chr> , K008 < chr> , K009 < chr> , TK001_01 < chr> ,
## # TK001_02 < chr> , TK001_03 < chr> , TK001_04 < chr> , TK002_01 < chr> ,
## # TK002_02 < chr> , TK002_03 < chr> , TK002_04 < chr> , TK003_01 < chr> ,
## # TK003_02 < chr> , TK003_03 < chr> , TK003_04 < chr> , TK004_01 < chr> ,
## # TK004_02 < chr> , TK004_03 < chr> , TK004_04 < chr> , TK005_01 < chr> , …< / code > < / pre >
< / div >
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< div id = "head" class = "section level3" number = "3.2.4" >
< h3 > < span class = "header-section-number" > 3.2.4< / span > Head< / h3 >
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< pre class = "r" > < code > head(litdata)< / code > < / pre >
< pre > < code > ## # A tibble: 6 ×
## id submitd…¹ lastp…² start…³ seed start…⁴ dates…⁵ W001 W002 W003 W004
## < dbl> < chr> < dbl> < chr> < dbl> < chr> < chr> < chr> < chr> < chr> < chr>
## 1 1 10/25/20… 5 en 6.65e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 2 2 < NA> NA de 3.34e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 3 3 < NA> NA de 6.84e8 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## 4 5 < NA> 2 de 2.08e9 10/25/… 10/25/… Stim… Stim… 4 Stim…
## 5 6 < NA> 2 en 4.38e8 10/25/… 10/25/… 3 3 3 Stim…
## 6 7 < NA> NA de 2.15e9 10/25/… 10/25/… < NA> < NA> < NA> < NA>
## # … with 55 more variables: W005 < chr> , W006 < chr> , W007 < chr> , W008 < chr> ,
## # W009 < chr> , K001 < chr> , K002 < chr> , K003 < chr> , K004 < chr> , K005 < chr> ,
## # K006 < chr> , K007 < chr> , K008 < chr> , K009 < chr> , TK001_01 < chr> ,
## # TK001_02 < chr> , TK001_03 < chr> , TK001_04 < chr> , TK002_01 < chr> ,
## # TK002_02 < chr> , TK002_03 < chr> , TK002_04 < chr> , TK003_01 < chr> ,
## # TK003_02 < chr> , TK003_03 < chr> , TK003_04 < chr> , TK004_01 < chr> ,
## # TK004_02 < chr> , TK004_03 < chr> , TK004_04 < chr> , TK005_01 < chr> , …< / code > < / pre >
< / div >
< / div >
< / div >
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< div id = "data-cleaning" class = "section level1" number = "4" >
< h1 > < span class = "header-section-number" > 4< / span > Data cleaning< / h1 >
< div id = "converting-strings-to-numbers-and-keine-antwort-zu-nan" class = "section level2" number = "4.1" >
< h2 > < span class = "header-section-number" > 4.1< / span > Converting Strings to
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numbers and < em > Keine Antwort< / em > zu < em > NaN< / em > < / h2 >
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< pre class = "r" > < code > litdata < - litdata %> %
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mutate_all(~ replace(., . == " Stimme voll zu5" , 5)) %> %
mutate_all(~ replace(., . == " Stimme überhaupt nicht zu1" , 1)) %> %
mutate_all(~ replace(., . == " Keine Antwort-" , NaN))< / code > < / pre >
< / div >
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< div id = "make-it-numeric" class = "section level2" number = "4.2" >
< h2 > < span class = "header-section-number" > 4.2< / span > Make it numeric< / h2 >
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< p > The following code will < strong > NOT< / strong > be run. The Idea is to
show a way to automatically edit all columns. It works but some columns
are NOT numeric.< / p >
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< pre class = "r" > < code > # All colnames that exist
litdataColnames < - colnames(litdata)
# the ones we don' t want to change
litdataNonNumericCols < - c(" submitdate" , " startlanguage" , " startdate" , " datestamp" , " lastpage" , " seed" )
# the colnames that should be changed
litdataColsToMakeNumeric < - litdataColnames[!(litdataColnames %in% litdataNonNumericCols)]
print(litdataColsToMakeNumeric)
litdataColsToMakeNumeric < - c(" R1" )
for (col in litdataColsToMakeNumeric) {
litdata[[col]] < - as.numeric(litdata[[col]])
}< / code > < / pre >
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< p > First we rename all the columns< / p >
< pre class = "r" > < code > litdata < - litdata %> % rename(
" A1" = " W001" ,
" A2" = " W002" ,
" A3" = " W003" ,
" A4" = " W004" ,
" A5" = " W005" ,
" A6" = " W006" ,
" A7" = " W007" ,
" A8" = " W008" ,
" A9" = " W009" ,
" B1" = " K001" ,
" B2" = " K002" ,
" B3" = " K003" ,
" B4" = " K004" ,
" B5" = " K005" ,
" B6" = " K006" ,
" B7" = " K007" ,
" B8" = " K008" ,
" B9" = " K009" ,
" C1_1" = " TK001_01" ,
" C1_2" = " TK001_02" ,
" C1_3" = " TK001_03" ,
" C1_4" = " TK001_04" ,
" C2_1" = " TK002_01" ,
" C2_2" = " TK002_02" ,
" C2_3" = " TK002_03" ,
" C2_4" = " TK002_04" ,
" C3_1" = " TK003_01" ,
" C3_2" = " TK003_02" ,
" C3_3" = " TK003_03" ,
" C3_4" = " TK003_04" ,
" C4_1" = " TK004_01" ,
" C4_2" = " TK004_02" ,
" C4_3" = " TK004_03" ,
" C4_4" = " TK004_04" ,
" C5_1" = " TK005_01" ,
" C5_2" = " TK005_02" ,
" C5_3" = " TK005_03" ,
" C5_4" = " TK005_04" ,
" C6_1" = " TK006_01" ,
" C6_2" = " TK006_02" ,
" C6_3" = " TK006_03" ,
" C6_4" = " TK006_04" ,
" D1_1" = " H001_001" ,
" D1_2" = " H001_002" ,
" D1_3" = " H001_003" ,
" D1_4" = " H001_004" ,
" D1_5" = " H001_005" ,
" D1_6" = " H001_006" ,
" D1_7" = " H001_007" ,
" D2" = " H002" ,
" D3" = " H003" ,
" D4" = " H004" ,
" D4_comment" = " H004_other" ,
" D5" = " H005" ,
" D5_comment" = " H005_other" ,
" D6" = " H006" ,
" D7" = " H007" ,
" D8" = " H008" ,
" E1" = " R1"
)< / code > < / pre >
< p > Then we change the datatype and fix the values< / p >
< pre class = "r" > < code > litdata$A1 < - as.numeric(litdata$A1)
litdata$A2 < - as.numeric(litdata$A2)
litdata$A3 < - as.numeric(litdata$A3)
litdata$A4 < - as.numeric(litdata$A4)
litdata$A5 < - as.numeric(litdata$A5)
litdata$A6 < - as.numeric(litdata$A6)
litdata$A7 < - as.numeric(litdata$A7)
litdata$A8 < - as.numeric(litdata$A8)
litdata$A9 < - as.numeric(litdata$A9)
litdata$B1 < - as.numeric(litdata$B1)
litdata$B2 < - as.numeric(litdata$B2)
litdata$B3 < - as.numeric(litdata$B3)
litdata$B4 < - as.numeric(litdata$B4)
litdata$B5 < - as.numeric(litdata$B5)
litdata$B6 < - as.numeric(litdata$B6)
litdata$B7 < - as.numeric(litdata$B7)
litdata$B8 < - as.numeric(litdata$B8)
litdata$B9 < - as.numeric(litdata$B9)
litdata$C1_1 < - as.numeric(litdata$C1_1)
litdata$C1_2 < - as.numeric(litdata$C1_2)
litdata$C1_3 < - as.numeric(litdata$C1_3)
litdata$C1_4 < - as.numeric(litdata$C1_4)
litdata$C2_1 < - as.numeric(litdata$C2_1)
litdata$C2_2 < - as.numeric(litdata$C2_2)
litdata$C2_3 < - as.numeric(litdata$C2_3)
litdata$C2_4 < - as.numeric(litdata$C2_4)
litdata$C3_1 < - as.numeric(litdata$C3_1)
litdata$C3_2 < - as.numeric(litdata$C3_2)
litdata$C3_3 < - as.numeric(litdata$C3_3)
litdata$C3_4 < - as.numeric(litdata$C3_4)
litdata$C4_1 < - as.numeric(litdata$C4_1)
litdata$C4_2 < - as.numeric(litdata$C4_2)
litdata$C4_3 < - as.numeric(litdata$C4_3)
litdata$C4_4 < - as.numeric(litdata$C4_4)
litdata$C5_1 < - as.numeric(litdata$C5_1)
litdata$C5_2 < - as.numeric(litdata$C5_2)
litdata$C5_3 < - as.numeric(litdata$C5_3)
litdata$C5_4 < - as.numeric(litdata$C5_4)
litdata$C6_1 < - as.numeric(litdata$C6_1)
litdata$C6_2 < - as.numeric(litdata$C6_2)
litdata$C6_3 < - as.numeric(litdata$C6_3)
litdata$C6_4 < - as.numeric(litdata$C6_4)
litdata < - litdata %> % mutate(D1_1 = ifelse(D1_1 == " Ja" , TRUE, ifelse(D1_1 == " Nicht Gewählt" , FALSE, D1_1)))
litdata$D1_1 < - as.logical(litdata$D1_1)
litdata < - litdata %> % mutate(D1_2 = ifelse(D1_2 == " Ja" , TRUE, ifelse(D1_2 == " Nicht Gewählt" , FALSE, D1_2)))
litdata$D1_2 < - as.logical(litdata$D1_2)
litdata < - litdata %> % mutate(D1_3 = ifelse(D1_3 == " Ja" , TRUE, ifelse(D1_3 == " Nicht Gewählt" , FALSE, D1_3)))
litdata$D1_3 < - as.logical(litdata$D1_3)
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litdata < - litdata %> % mutate(D1_4 = ifelse(D1_4 == " Ja" , TRUE, ifelse(D1_4 == " Nicht Gewählt" , FALSE, D1_4)))
litdata$D1_4 < - as.logical(litdata$D1_4)
litdata < - litdata %> % mutate(D1_5 = ifelse(D1_5 == " Ja" , TRUE, ifelse(D1_5 == " Nicht Gewählt" , FALSE, D1_5)))
litdata$D1_5 < - as.logical(litdata$D1_5)
litdata < - litdata %> % mutate(D1_6 = ifelse(D1_6 == " Ja" , TRUE, ifelse(D1_6 == " Nicht Gewählt" , FALSE, D1_6)))
litdata$D1_6 < - as.logical(litdata$D1_6)
litdata < - litdata %> % mutate(D1_7 = ifelse(D1_7 == " Ja" , TRUE, ifelse(D1_7 == " Nicht Gewählt" , FALSE, D1_7)))
litdata$D1_7 < - as.logical(litdata$D1_7)
litdata < - litdata %> % mutate(D2 = ifelse(D2 == " Ja" , TRUE, ifelse(D2 == " Nein" , FALSE, D2)))
litdata$D2 < - as.logical(litdata$D2)
# skipping D3 because it' s just a free text
litdata$D4 < - as.factor(litdata$D4)
# skipping D4_comment because it' s a free text
litdata$D5 < - as.factor(litdata$D5)
# skipping D5_comment because it' s a free text
# can' t be a number as there is a 2010 or earlier option.
litdata$D6 < - as.factor(litdata$D6)
litdata$D7 < - as.numeric(litdata$D7)
litdata$D8 < - as.factor(litdata$D8)
# skipping E1 because it' s a free text< / code > < / pre >
< / div >
2022-11-18 21:01:02 +01:00
< div id = "second-inspection-of-data" class = "section level2 tabset" number = "4.3" >
< h2 class = "tabset" > < span class = "header-section-number" > 4.3< / span > Second
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inspection of data< / h2 >
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< div id = "summary-1" class = "section level3" number = "4.3.1" >
< h3 > < span class = "header-section-number" > 4.3.1< / span > Summary< / h3 >
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< pre class = "r" > < code > summary(litdata)< / code > < / pre >
< pre > < code > ## id submitdate lastpage startlanguage
## Min. : 1 Length:313 Min. :-1.000 Length:313
## 1st Qu.: 81 Class :character 1st Qu.: 2.000 Class :character
## Median :162 Mode :character Median : 5.000 Mode :character
## Mean :163 Mean : 3.556
## 3rd Qu.:245 3rd Qu.: 5.000
## Max. :327 Max. : 5.000
## NA' s :108
## seed startdate datestamp A1
## Min. :5.647e+06 Length:313 Length:313 Min. :2.000
## 1st Qu.:5.568e+08 Class :character Class :character 1st Qu.:4.000
## Median :1.086e+09 Mode :character Mode :character Median :5.000
## Mean :1.081e+09 Mean :4.515
## 3rd Qu.:1.637e+09 3rd Qu.:5.000
## Max. :2.147e+09 Max. :5.000
## NA' s :117
## A2 A3 A4 A5
## Min. :1.000 Min. :2.000 Min. :1.000 Min. :2.000
## 1st Qu.:3.000 1st Qu.:4.000 1st Qu.:4.000 1st Qu.:4.000
## Median :4.000 Median :4.000 Median :5.000 Median :5.000
## Mean :3.955 Mean :4.246 Mean :4.523 Mean :4.411
## 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
## NA' s :114 NA' s :114 NA' s :114 NA' s :116
## A6 A7 A8 A9
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:4.000 1st Qu.:5.000 1st Qu.:3.000 1st Qu.:3.000
## Median :4.000 Median :5.000 Median :4.000 Median :4.000
## Mean :4.347 Mean :4.824 Mean :3.581 Mean :3.663
## 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
## NA' s :117 NA' s :114 NA' s :122 NA' s :120
## B1 B2 B3 B4
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :3.000 Median :3.000 Median :3.000 Median :3.000
## Mean :3.293 Mean :2.851 Mean :2.863 Mean :3.221
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
## NA' s :132 NA' s :132 NA' s :131 NA' s :132
## B5 B6 B7 B8 B9
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000
## 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.00 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :4.000 Median :3.00 Median :3.000
## Mean :3.409 Mean :2.956 Mean :3.522 Mean :2.72 Mean :2.657
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:3.75 3rd Qu.:3.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.00 Max. :5.000
## NA' s :132 NA' s :132 NA' s :131 NA' s :131 NA' s :132
## C1_1 C1_2 C1_3 C1_4
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:4.000 1st Qu.:4.000 1st Qu.:2.000
## Median :4.000 Median :4.000 Median :5.000 Median :3.000
## Mean :3.606 Mean :4.153 Mean :4.336 Mean :2.956
## 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
## NA' s :204 NA' s :202 NA' s :200 NA' s :200
## C2_1 C2_2 C2_3 C2_4
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:4.000 1st Qu.:4.000 1st Qu.:2.000
## Median :3.000 Median :4.000 Median :5.000 Median :3.000
## Mean :3.409 Mean :4.055 Mean :4.279 Mean :3.071
## 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
## NA' s :203 NA' s :204 NA' s :202 NA' s :201
## C3_1 C3_2 C3_3 C3_4 C4_1
## Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:4.000 1st Qu.:4.00 1st Qu.:3.000 1st Qu.:3.000
## Median :3.000 Median :4.000 Median :5.00 Median :3.000 Median :4.000
## Mean :3.495 Mean :4.189 Mean :4.42 Mean :3.321 Mean :3.759
## 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:5.00 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.00 Max. :5.000 Max. :5.000
## NA' s :202 NA' s :202 NA' s :201 NA' s :201 NA' s :201
## C4_2 C4_3 C4_4 C5_1 C5_2
## Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000 Min. :1.000
## 1st Qu.:4.000 1st Qu.:4.000 1st Qu.:3.00 1st Qu.:3.000 1st Qu.:4.000
## Median :5.000 Median :5.000 Median :3.00 Median :4.000 Median :4.000
## Mean :4.279 Mean :4.396 Mean :3.33 Mean :3.727 Mean :4.183
## 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:4.00 3rd Qu.:5.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.00 Max. :5.000 Max. :5.000
## NA' s :202 NA' s :202 NA' s :201 NA' s :203 NA' s :204
## C5_3 C5_4 C6_1 C6_2
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:4.000 1st Qu.:3.000 1st Qu.:3.000 1st Qu.:4.000
## Median :5.000 Median :3.000 Median :4.000 Median :4.000
## Mean :4.369 Mean :3.255 Mean :3.609 Mean :4.136
## 3rd Qu.:5.000 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
## NA' s :202 NA' s :203 NA' s :203 NA' s :203
## C6_3 C6_4 D1_1 D1_2
## Min. :1.000 Min. :1.000 Mode :logical Mode :logical
## 1st Qu.:4.000 1st Qu.:3.000 FALSE:64 FALSE:69
## Median :5.000 Median :3.000 TRUE :51 TRUE :46
## Mean :4.245 Mean :3.191 NA' s :198 NA' s :198
## 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000
## NA' s :203 NA' s :203
## D1_3 D1_4 D1_5 D1_6
## Mode :logical Mode :logical Mode :logical Mode :logical
## FALSE:30 FALSE:81 FALSE:108 FALSE:115
## TRUE :85 TRUE :34 TRUE :7 NA' s :198
## NA' s :198 NA' s :198 NA' s :198
##
##
##
## D1_7 D2 D3
## Mode :logical Mode :logical Length:313
## FALSE:115 FALSE:12 Class :character
## NA' s :198 TRUE :103 Mode :character
## NA' s :198
##
##
##
## D4
## Berufe des Managements und der Administration, des Bank- und Versicherungsgewerbes und des Rechtswesens: 29
## Gesundheits-, Lehr- und Kulturberufe, Wissenschaftler : 24
## Technische Berufe sowie Informatikberufe : 24
## Berufe des Gastgewerbes und Berufe zur Erbringung persönlicher Dienstleistungens- und Verkehrsberufe : 13
## - : 8
## (Other) : 5
## NA' s :210
## D4_comment D5 D5_comment
## Length:313 Bachelor Information Science : 40 Min. : NA
## Class :character Master Information and Data Management: 10 1st Qu.: NA
## Mode :character Bachelor Multimedia Production : 8 Median : NA
## Bachelor Tourismus : 8 Mean :NaN
## Bachelor Betriebsökonomie : 7 3rd Qu.: NA
## (Other) : 40 Max. : NA
## NA' s :200 NA' s :313
## D6 D7 D8 E1
## 2020 : 34 Min. :1971 männlich: 39 Length:313
## 2018 : 26 1st Qu.:1991 Weiblich: 75 Class :character
## 2021 : 25 Median :1995 NA' s :199 Mode :character
## 2019 : 20 Mean :1993
## 2017 : 4 3rd Qu.:1998
## (Other): 3 Max. :2002
## NA' s :201 NA' s :207< / code > < / pre >
< / div >
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< div id = "glimpse-1" class = "section level3" number = "4.3.2" >
< h3 > < span class = "header-section-number" > 4.3.2< / span > Glimpse< / h3 >
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< pre class = "r" > < code > glimpse(litdata)< / code > < / pre >
< pre > < code > ## Rows: 313
## Columns: 66
## $ id < dbl> 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, …
## $ submitdate < chr> " 10/25/2021 11:07:44" , NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ lastpage < dbl> 5, NA, NA, 2, 2, NA, NA, NA, 2, 1, NA, NA, 5, NA, NA, NA…
## $ startlanguage < chr> " en" , " de" , " de" , " de" , " en" , " de" , " de" , " de" , " en" , " d…
## $ seed < dbl> 664891087, 334145431, 683903577, 2082427237, 438283320, …
## $ startdate < chr> " 10/25/2021 11:07:40" , " 10/25/2021 11:33:06" , " 10/25/202…
## $ datestamp < chr> " 10/25/2021 11:07:44" , " 10/25/2021 11:33:06" , " 10/25/202…
## $ A1 < dbl> NA, NA, NA, 5, 3, NA, NA, NA, 5, 3, NA, NA, 5, NA, NA, N…
## $ A2 < dbl> NA, NA, NA, 5, 3, NA, NA, NA, 4, 2, NA, NA, 5, NA, NA, N…
## $ A3 < dbl> NA, NA, NA, 4, 3, NA, NA, NA, 4, 4, NA, NA, 5, NA, NA, N…
## $ A4 < dbl> NA, NA, NA, 5, 5, NA, NA, NA, 4, 4, NA, NA, 5, NA, NA, N…
## $ A5 < dbl> NA, NA, NA, 5, 5, NA, NA, NA, 4, 4, NA, NA, 4, NA, NA, N…
## $ A6 < dbl> NA, NA, NA, 4, 4, NA, NA, NA, 4, 4, NA, NA, 4, NA, NA, N…
## $ A7 < dbl> NA, NA, NA, 4, 5, NA, NA, NA, 5, 3, NA, NA, 5, NA, NA, N…
## $ A8 < dbl> NA, NA, NA, 5, 4, NA, NA, NA, 5, 4, NA, NA, 5, NA, NA, N…
## $ A9 < dbl> NA, NA, NA, 5, 5, NA, NA, NA, 5, 5, NA, NA, 5, NA, NA, N…
## $ B1 < dbl> NA, NA, NA, 4, 4, NA, NA, NA, 4, NA, NA, NA, 3, NA, NA, …
## $ B2 < dbl> NA, NA, NA, 3, 3, NA, NA, NA, 4, NA, NA, NA, 4, NA, NA, …
## $ B3 < dbl> NA, NA, NA, 3, 5, NA, NA, NA, 3, NA, NA, NA, 4, NA, NA, …
## $ B4 < dbl> NA, NA, NA, 3, 4, NA, NA, NA, 4, NA, NA, NA, 3, NA, NA, …
## $ B5 < dbl> NA, NA, NA, 4, 3, NA, NA, NA, 4, NA, NA, NA, 3, NA, NA, …
## $ B6 < dbl> NA, NA, NA, 4, 4, NA, NA, NA, 4, NA, NA, NA, 4, NA, NA, …
## $ B7 < dbl> NA, NA, NA, 4, 3, NA, NA, NA, 3, NA, NA, NA, 4, NA, NA, …
## $ B8 < dbl> NA, NA, NA, 4, 3, NA, NA, NA, 4, NA, NA, NA, 5, NA, NA, …
## $ B9 < dbl> NA, NA, NA, 4, 2, NA, NA, NA, 4, NA, NA, NA, 5, NA, NA, …
## $ C1_1 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ C1_2 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C1_3 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C1_4 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ C2_1 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ C2_2 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C2_3 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C2_4 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ C3_1 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, N…
## $ C3_2 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ C3_3 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C3_4 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C4_1 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C4_2 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C4_3 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C4_4 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ C5_1 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C5_2 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C5_3 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C5_4 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C6_1 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C6_2 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C6_3 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, NA, N…
## $ C6_4 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, N…
## $ D1_1 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, TRUE, NA…
## $ D1_2 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, N…
## $ D1_3 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, TRUE, NA…
## $ D1_4 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, N…
## $ D1_5 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, N…
## $ D1_6 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, N…
## $ D1_7 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, N…
## $ D2 < lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, TRUE, NA…
## $ D3 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Bibliot…
## $ D4 < fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Gesundh…
## $ D4_comment < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ D5 < fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, Bachelor…
## $ D5_comment < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ D6 < fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ D7 < dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ D8 < fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, Weiblich…
## $ E1 < chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, " Die Fra…< / code > < / pre >
< / div >
2022-11-18 21:01:02 +01:00
< div id = "print-1" class = "section level3" number = "4.3.3" >
< h3 > < span class = "header-section-number" > 4.3.3< / span > Print< / h3 >
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< pre class = "r" > < code > print(litdata)< / code > < / pre >
< pre > < code > ## # A tibble: 313 ×
## id submit…¹ lastp…² start…³ seed start…⁴ dates…⁵ A1 A2 A3 A4
## < dbl> < chr> < dbl> < chr> < dbl> < chr> < chr> < dbl> < dbl> < dbl> < dbl>
## 1 1 10/25/2… 5 en 6.65e8 10/25/… 10/25/… NA NA NA NA
## 2 2 < NA> NA de 3.34e8 10/25/… 10/25/… NA NA NA NA
## 3 3 < NA> NA de 6.84e8 10/25/… 10/25/… NA NA NA NA
## 4 5 < NA> 2 de 2.08e9 10/25/… 10/25/… 5 5 4 5
## 5 6 < NA> 2 en 4.38e8 10/25/… 10/25/… 3 3 3 5
## 6 7 < NA> NA de 2.15e9 10/25/… 10/25/… NA NA NA NA
## 7 8 < NA> NA de 1.74e9 10/25/… 10/25/… NA NA NA NA
## 8 9 < NA> NA de 4.64e8 10/25/… 10/25/… NA NA NA NA
## 9 10 < NA> 2 en 1.09e9 10/25/… 10/25/… 5 4 4 4
## 10 11 < NA> 1 de 1.55e9 10/25/… 10/25/… 3 2 4 4
## # … with 303 more rows, 55 more variables: A5 < dbl> , A6 < dbl> , A7 < dbl> ,
## # A8 < dbl> , A9 < dbl> , B1 < dbl> , B2 < dbl> , B3 < dbl> , B4 < dbl> , B5 < dbl> ,
## # B6 < dbl> , B7 < dbl> , B8 < dbl> , B9 < dbl> , C1_1 < dbl> , C1_2 < dbl> , C1_3 < dbl> ,
## # C1_4 < dbl> , C2_1 < dbl> , C2_2 < dbl> , C2_3 < dbl> , C2_4 < dbl> , C3_1 < dbl> ,
## # C3_2 < dbl> , C3_3 < dbl> , C3_4 < dbl> , C4_1 < dbl> , C4_2 < dbl> , C4_3 < dbl> ,
## # C4_4 < dbl> , C5_1 < dbl> , C5_2 < dbl> , C5_3 < dbl> , C5_4 < dbl> , C6_1 < dbl> ,
## # C6_2 < dbl> , C6_3 < dbl> , C6_4 < dbl> , D1_1 < lgl> , D1_2 < lgl> , D1_3 < lgl> , …< / code > < / pre >
< / div >
2022-11-18 21:01:02 +01:00
< div id = "head-1" class = "section level3" number = "4.3.4" >
< h3 > < span class = "header-section-number" > 4.3.4< / span > Head< / h3 >
2022-11-18 09:14:50 +01:00
< pre class = "r" > < code > head(litdata)< / code > < / pre >
< pre > < code > ## # A tibble: 6 ×
## id submitd…¹ lastp…² start…³ seed start…⁴ dates…⁵ A1 A2 A3 A4
## < dbl> < chr> < dbl> < chr> < dbl> < chr> < chr> < dbl> < dbl> < dbl> < dbl>
## 1 1 10/25/20… 5 en 6.65e8 10/25/… 10/25/… NA NA NA NA
## 2 2 < NA> NA de 3.34e8 10/25/… 10/25/… NA NA NA NA
## 3 3 < NA> NA de 6.84e8 10/25/… 10/25/… NA NA NA NA
## 4 5 < NA> 2 de 2.08e9 10/25/… 10/25/… 5 5 4 5
## 5 6 < NA> 2 en 4.38e8 10/25/… 10/25/… 3 3 3 5
## 6 7 < NA> NA de 2.15e9 10/25/… 10/25/… NA NA NA NA
## # … with 55 more variables: A5 < dbl> , A6 < dbl> , A7 < dbl> , A8 < dbl> , A9 < dbl> ,
## # B1 < dbl> , B2 < dbl> , B3 < dbl> , B4 < dbl> , B5 < dbl> , B6 < dbl> , B7 < dbl> ,
## # B8 < dbl> , B9 < dbl> , C1_1 < dbl> , C1_2 < dbl> , C1_3 < dbl> , C1_4 < dbl> ,
## # C2_1 < dbl> , C2_2 < dbl> , C2_3 < dbl> , C2_4 < dbl> , C3_1 < dbl> , C3_2 < dbl> ,
## # C3_3 < dbl> , C3_4 < dbl> , C4_1 < dbl> , C4_2 < dbl> , C4_3 < dbl> , C4_4 < dbl> ,
## # C5_1 < dbl> , C5_2 < dbl> , C5_3 < dbl> , C5_4 < dbl> , C6_1 < dbl> , C6_2 < dbl> ,
## # C6_3 < dbl> , C6_4 < dbl> , D1_1 < lgl> , D1_2 < lgl> , D1_3 < lgl> , D1_4 < lgl> , …< / code > < / pre >
< / div >
< / div >
< / div >
2022-11-18 21:01:02 +01:00
< div id = "selbststudium-1" class = "section level1" number = "5" >
< h1 > < span class = "header-section-number" > 5< / span > Selbststudium 1< / h1 >
2022-11-18 09:14:50 +01:00
< p > < em > Berechnen Sie die Häufigkeiten für die Variablen W003, K003,
H001_001, H005, H007 und H008.< / em > < / p >
2022-11-18 21:01:02 +01:00
< div id = "data" class = "section level2 tabset" number = "5.1" >
< h2 class = "tabset" > < span class = "header-section-number" > 5.1< / span >
2022-11-18 09:14:50 +01:00
Data< / h2 >
< pre class = "r" > < code > displayFunction1 < - function(table, column) {
tmp < - table[column]
tmp < - rename(tmp, value = all_of(column))
tmp < - tmp %> %
count(value) %> %
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mutate(percentage = prop.table(n) * 100)
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print(tmp, n = 100)
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ggplot(
tmp,
aes(x = value, y = n)
) +
geom_bar(stat = " identity" ) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
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}< / code > < / pre >
< div id = "a3-w003" class = "section level3 unnumbered" >
< h3 class = "unnumbered" > A3 (W003)< / h3 >
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< pre class = "r" > < code > displayFunction1(litdata, " A3" )< / code > < / pre >
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< pre > < code > ## # A tibble: 6 ×
## value n percentage
## < dbl> < int> < dbl>
## 1 2 6 1.92
## 2 3 29 9.27
## 3 4 74 23.6
## 4 5 90 28.8
## 5 NA 112 35.8
## 6 NaN 2 0.639< / code > < / pre >
< pre > < code > ## Warning: Removed 2 rows containing missing values (`position_stack()`).< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "b3-k003" class = "section level3 unnumbered" >
< h3 class = "unnumbered" > B3 (K003)< / h3 >
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< pre class = "r" > < code > displayFunction1(litdata, " B3" )< / code > < / pre >
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< pre > < code > ## # A tibble: 7 ×
## value n percentage
## < dbl> < int> < dbl>
## 1 1 16 5.11
## 2 2 47 15.0
## 3 3 71 22.7
## 4 4 42 13.4
## 5 5 6 1.92
## 6 NA 130 41.5
## 7 NaN 1 0.319< / code > < / pre >
< pre > < code > ## Warning: Removed 2 rows containing missing values (`position_stack()`).< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "d1_1-h001_001" class = "section level3 unnumbered" >
< h3 class = "unnumbered" > D1_1 (H001_001)< / h3 >
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< pre class = "r" > < code > displayFunction1(litdata, " D1_1" )< / code > < / pre >
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< pre > < code > ## # A tibble: 3 ×
## value n percentage
## < lgl> < int> < dbl>
## 1 FALSE 64 20.4
## 2 TRUE 51 16.3
## 3 NA 198 63.3< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "d5-h005" class = "section level3 unnumbered" >
< h3 class = "unnumbered" > D5 (H005)< / h3 >
2022-11-18 21:10:07 +01:00
< pre class = "r" > < code > displayFunction1(litdata, " D5" )< / code > < / pre >
2022-11-18 09:14:50 +01:00
< pre > < code > ## # A tibble: 18 ×
## value n percentage
## < fct> < int> < dbl>
## 1 Bachelor Architektur 1 0.319
## 2 Bachelor Bauingenieurwesen 2 0.639
## 3 Bachelor Betriebsökonomie 7 2.24
## 4 Bachelor Computational and Data Science 2 0.639
## 5 Bachelor Digital Business Management 6 1.92
## 6 Bachelor Information Science 40 12.8
## 7 Bachelor Mobile Robotics 1 0.319
## 8 Bachelor Multimedia Production 8 2.56
## 9 Bachelor Photonics 3 0.958
## 10 Bachelor Service Innovation and Design 5 1.60
## 11 Bachelor Sport Management 7 2.24
## 12 Bachelor Tourismus 8 2.56
## 13 CAS Sport Management 4.0 1 0.319
## 14 MAS Information Science 1 0.319
## 15 Master Information and Data Management 10 3.19
## 16 Master New Business 7 2.24
## 17 Master Tourism and Change 4 1.28
## 18 < NA> 200 63.9< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "d7-h007" class = "section level3 unnumbered" >
< h3 class = "unnumbered" > D7 (H007)< / h3 >
2022-11-18 21:10:07 +01:00
< pre class = "r" > < code > displayFunction1(litdata, " D7" )< / code > < / pre >
2022-11-18 09:14:50 +01:00
< pre > < code > ## # A tibble: 24 ×
## value n percentage
## < dbl> < int> < dbl>
## 1 1971 1 0.319
## 2 1972 1 0.319
## 3 1973 1 0.319
## 4 1974 3 0.958
## 5 1980 1 0.319
## 6 1984 1 0.319
## 7 1985 4 1.28
## 8 1987 5 1.60
## 9 1988 3 0.958
## 10 1989 2 0.639
## 11 1990 4 1.28
## 12 1991 5 1.60
## 13 1992 6 1.92
## 14 1993 8 2.56
## 15 1994 2 0.639
## 16 1995 10 3.19
## 17 1996 3 0.958
## 18 1997 14 4.47
## 19 1998 15 4.79
## 20 1999 7 2.24
## 21 2000 7 2.24
## 22 2001 2 0.639
## 23 2002 1 0.319
## 24 NA 207 66.1< / code > < / pre >
< pre > < code > ## Warning: Removed 1 rows containing missing values (`position_stack()`).< / code > < / pre >
< p > < img src = "data:image/png;base64,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< p > Die Warnung resultiert daraus, dass es sehr viele < em > NA< / em >
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gibt.< / p >
< / div >
< div id = "d8-h008" class = "section level3 unnumbered" >
< h3 class = "unnumbered" > D8 (H008)< / h3 >
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< pre class = "r" > < code > displayFunction1(litdata, " D8" )< / code > < / pre >
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< pre > < code > ## # A tibble: 3 ×
## value n percentage
## < fct> < int> < dbl>
## 1 männlich 39 12.5
## 2 Weiblich 75 24.0
## 3 < NA> 199 63.6< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< / div >
< / div >
2022-11-18 21:01:02 +01:00
< div id = "selbststudium-2.1" class = "section level1" number = "6" >
< h1 > < span class = "header-section-number" > 6< / span > Selbststudium 2.1< / h1 >
< p > We have the year 2021 ## Preparation< / p >
< pre class = "r" > < code > birthyears < - litdata$D7
# remove NAs
birthyears < - birthyears[!is.na(birthyears)]
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age < - 2021 - birthyears< / code > < / pre >
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< div id = "frequency" class = "section level2" number = "6.1" >
< h2 > < span class = "header-section-number" > 6.1< / span > Frequency< / h2 >
< pre class = "r" > < code > freq(age)< / code > < / pre >
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< pre > < code > ## frequency percent valid_percent cumulative_percent
## 19 1 0.94 0.94 0.94
## 20 2 1.89 1.89 2.83
## 21 7 6.60 6.60 9.43
## 22 7 6.60 6.60 16.04
## 23 15 14.15 14.15 30.19
## 24 14 13.21 13.21 43.40
## 25 3 2.83 2.83 46.23
## 26 10 9.43 9.43 55.66
## 27 2 1.89 1.89 57.55
## 28 8 7.55 7.55 65.09
## 29 6 5.66 5.66 70.75
## 30 5 4.72 4.72 75.47
## 31 4 3.77 3.77 79.25
## 32 2 1.89 1.89 81.13
## 33 3 2.83 2.83 83.96
## 34 5 4.72 4.72 88.68
## 36 4 3.77 3.77 92.45
## 37 1 0.94 0.94 93.40
## 41 1 0.94 0.94 94.34
## 47 3 2.83 2.83 97.17
## 48 1 0.94 0.94 98.11
## 49 1 0.94 0.94 99.06
## 50 1 0.94 0.94 100.00
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## Valid_Total 106 100.00 100.00 NaN
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## NAs 0 0.00 NaN NaN
## Total 106 100.00 NaN NaN< / code > < / pre >
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< pre class = "r" > < code > # with NA
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freq(2021 - litdata$D7)< / code > < / pre >
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< pre > < code > ## frequency percent valid_percent cumulative_percent
## 19 1 0.32 0.94 0.94
## 20 2 0.64 1.89 2.83
## 21 7 2.24 6.60 9.43
## 22 7 2.24 6.60 16.04
## 23 15 4.79 14.15 30.19
## 24 14 4.47 13.21 43.40
## 25 3 0.96 2.83 46.23
## 26 10 3.19 9.43 55.66
## 27 2 0.64 1.89 57.55
## 28 8 2.56 7.55 65.09
## 29 6 1.92 5.66 70.75
## 30 5 1.60 4.72 75.47
## 31 4 1.28 3.77 79.25
## 32 2 0.64 1.89 81.13
## 33 3 0.96 2.83 83.96
## 34 5 1.60 4.72 88.68
## 36 4 1.28 3.77 92.45
## 37 1 0.32 0.94 93.40
## 41 1 0.32 0.94 94.34
## 47 3 0.96 2.83 97.17
## 48 1 0.32 0.94 98.11
## 49 1 0.32 0.94 99.06
## 50 1 0.32 0.94 100.00
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## Valid_Total 106 33.87 100.00 NaN
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## NAs 207 66.13 NaN NaN
## Total 313 100.00 NaN NaN< / code > < / pre >
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< / div >
< div id = "selbststudium-2" class = "section level2" number = "6.2" >
< h2 > < span class = "header-section-number" > 6.2< / span > Selbststudium 2< / h2 >
< p > < a href = "https://www.beratung-statistik.de/statistik-beratung-infos/r-tutorial/deskriptive-statistik-r/" class = "uri" > https://www.beratung-statistik.de/statistik-beratung-infos/r-tutorial/deskriptive-statistik-r/< / a > < / p >
< div id = "modalwert" class = "section level3" number = "6.2.1" >
< h3 > < span class = "header-section-number" > 6.2.1< / span > Modalwert< / h3 >
< pre class = "r" > < code > # own method
getmode(age)< / code > < / pre >
< pre > < code > ## [1] 23< / code > < / pre >
< / div >
< div id = "median" class = "section level3" number = "6.2.2" >
< h3 > < span class = "header-section-number" > 6.2.2< / span > Median< / h3 >
< pre class = "r" > < code > median(age)< / code > < / pre >
< pre > < code > ## [1] 26< / code > < / pre >
< / div >
< div id = "arithmetischer-mittelwert" class = "section level3" number = "6.2.3" >
< h3 > < span class = "header-section-number" > 6.2.3< / span > Arithmetischer
Mittelwert< / h3 >
< pre class = "r" > < code > mean(age)< / code > < / pre >
< pre > < code > ## [1] 27.78302< / code > < / pre >
< / div >
< div id = "spannweite" class = "section level3" number = "6.2.4" >
< h3 > < span class = "header-section-number" > 6.2.4< / span > Spannweite< / h3 >
2022-11-18 21:10:07 +01:00
< pre class = "r" > < code > max(age) - min(age)< / code > < / pre >
2022-11-18 21:01:02 +01:00
< pre > < code > ## [1] 31< / code > < / pre >
< / div >
< div id = "quartilsabstand" class = "section level3" number = "6.2.5" >
< h3 > < span class = "header-section-number" > 6.2.5< / span >
Quartilsabstand< / h3 >
< pre class = "r" > < code > IQR(age)< / code > < / pre >
< pre > < code > ## [1] 7< / code > < / pre >
< pre class = "r" > < code > # just for fun
summary(age)< / code > < / pre >
< pre > < code > ## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 19.00 23.00 26.00 27.78 30.00 50.00< / code > < / pre >
< / div >
< div id = "varianz" class = "section level3" number = "6.2.6" >
< h3 > < span class = "header-section-number" > 6.2.6< / span > Varianz< / h3 >
< pre class = "r" > < code > var(age)< / code > < / pre >
< pre > < code > ## [1] 45.04771< / code > < / pre >
< / div >
< div id = "standardabweichung" class = "section level3" number = "6.2.7" >
< h3 > < span class = "header-section-number" > 6.2.7< / span >
Standardabweichung< / h3 >
< pre class = "r" > < code > sd(age)< / code > < / pre >
< pre > < code > ## [1] 6.711759< / code > < / pre >
< / div >
< div id = "schiefe" class = "section level3" number = "6.2.8" >
< h3 > < span class = "header-section-number" > 6.2.8< / span > Schiefe< / h3 >
2022-12-02 14:03:44 +01:00
< pre class = "r" > < code > skewness(age)< / code > < / pre >
< pre > < code > ## [1] 1.550033< / code > < / pre >
2022-11-18 21:01:02 +01:00
< blockquote >
< p > Die Kennzahl Schiefe ist wird Null bei einer perfekt symmetrischen
Verteilung, größer als Null bei einer rechtsschiefen und kleiner als
Null bei einer linksschiefen Verteilung. < a href = "https://www.beratung-statistik.de/statistik-beratung-infos/r-tutorial/deskriptive-statistik-r/" class = "uri" > https://www.beratung-statistik.de/statistik-beratung-infos/r-tutorial/deskriptive-statistik-r/< / a > < / p >
< / blockquote >
< / div >
< div id = "kurtosis" class = "section level3" number = "6.2.9" >
< h3 > < span class = "header-section-number" > 6.2.9< / span > Kurtosis< / h3 >
2022-12-02 14:03:44 +01:00
< pre class = "r" > < code > kurtosis(age, type = 2) # https://rdrr.io/rforge/e1071/man/kurtosis.html< / code > < / pre >
< pre > < code > ## [1] 2.55861< / code > < / pre >
2022-11-18 21:01:02 +01:00
< blockquote >
< p > Eine weitere bekannte Kennzahl ist die Kurtosis. Um eine Vorstellung
von der Bedeutung der Kurtosis zu erhalten, betrachten Sie nachfolgende
Graphik.< br / >
In dieser Graphik sind eine Normalverteilung, sowie eine steilgipflige
(aka leptokurtisch) und eine flachgipflige (aka platykurtisch)
dargestellt. Die steilgipflige Verteilung ist in der Mitte spitzer als
die Normalverteilung und an den Rändern breiter. Bei der flachgipligen
Verteilung ist es anders herum. Die Kurtosis ist nun eine Kennzahl, mit
der untersucht wird, ob eine Verteilung im Vergleich zur
Normalverteilung flachgipflig oder steilgipflig ist:< br / >
- Für eine Normalverteilung nimmt die Kurtosis genau den Wert 3
an.< br / >
- Eine steilgipflige Verteilung hat eine Kurtosis, die größer als 3
ist.< br / >
- Für eine flachgipflige Verteilung ist die Kurtosis kleiner als
3.< br / >
- Beachten Sie: Anstatt der Kurtosis wird häufig auch der sogenannte
Exzess verwendet. Dies ist eine weitere Kennzahl, die definiert ist
durch die Formel: Exzess = Kurtosis - 3.< br / >
- Der Exzess ist somit größer als Null, wenn die Verteilung steilgipflig
ist, und kleiner als Null bei einer flachgipfligen Verteilung.< br / >
< img src = "data:image/png;base64,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
Frech kopiert von: < a href = "https://www.beratung-statistik.de/statistik-beratung-infos/r-tutorial/deskriptive-statistik-r/" class = "uri" > https://www.beratung-statistik.de/statistik-beratung-infos/r-tutorial/deskriptive-statistik-r/< / a > < / p >
< / blockquote >
< / div >
< div id = "qq-plot" class = "section level3" number = "6.2.10" >
< h3 > < span class = "header-section-number" > 6.2.10< / span > QQ-Plot< / h3 >
< pre class = "r" > < code > qqnorm(age)
qqline(age)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "historam-for-age" class = "section level3 tabset" number = "6.2.11" >
< h3 class = "tabset" > < span class = "header-section-number" > 6.2.11< / span >
Historam for age< / h3 >
2022-11-25 16:31:02 +01:00
< div id = "frequency-1" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > Frequency< / h4 >
< pre class = "r" > < code > hist(age, freq = F)
lines(density(age), lwd = 2, col = " black" )< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
2022-11-18 21:01:02 +01:00
< div id = "auto-breaks" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > Auto Breaks< / h4 >
< pre class = "r" > < code > hist(age)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 3 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 3)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks-1" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 5 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 5)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks-2" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 7 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 7)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks-3" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 10 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 10)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks-4" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 15 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 15)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks-5" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 20 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 20)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< div id = "breaks-6" class = "section level4 unnumbered" >
< h4 class = "unnumbered" > 30 Breaks< / h4 >
< pre class = "r" > < code > hist(age, breaks = 30)< / code > < / pre >
< p > < img src = "data:image/png;base64,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
< / div >
< / div >
< / div >
< / div >
< div id = "selbststudium-2.2" class = "section level1" number = "7" >
< h1 > < span class = "header-section-number" > 7< / span > Selbststudium 2.2< / h1 >
< p > Auf der Grundlage von Daten aus einer Schweizer Schüllererhebung wird
aus verschiedenen Variablen (z.B. Angaben zum Beruf der Eltern, zur
Elternausbildung sowie zur Anzahl von Bücchern zu Hause) ein Index zur
sozialen Herkunft erstellt. Dieser Index erscheint in einer neu
gebildeten numerischen Variable im Datensatz, gibt also für jeden Fall
in diesem Datensatz einen Skalenwert zur sozialen Herkunft an. Die neu
gebildete Skala läuft von 0 (Wert mit der geringsten Ausprägung) bis 10
(Wert mit der höchsten Ausprägung).< / p >
< p > Für die gesamte Schweiz liegt der arithmetische Mittelwert auf dieser
Skala bei 5.6 und die Standardabweichung beträgt 1.8 (Zahlen sind von
mir frei erfunden!). Die Verteilung entspricht einer
Normalverteilung.< / p >
< p > Der Mittelwert der Verteilung der Bündner Schüler liegt etwas tiefer
als in der Gesamtschweiz, nämlich bei 5.1 mit einer Standardabweichung
von 2.< / p >
< div id = "aufgabenstellung-1" class = "section level2" number = "7.1" >
< h2 > < span class = "header-section-number" > 7.1< / span > Aufgabenstellung
1< / h2 >
< p > Wo in der Verteilung der Schweiz liegt der Bündner Mittelwert, bzw.
wie viele Schweizer Schüler haben bzgl. der sozialen Herkunft einen
tieferen Wert als der typische Bündner Schüler?< / p >
< pre class = "r" > < code > pnorm(5.1, mean = 5.6, sd = 1.8)< / code > < / pre >
< pre > < code > ## [1] 0.3905915< / code > < / pre >
< / div >
< div id = "aufgabenstellung-2" class = "section level2" number = "7.2" >
< h2 > < span class = "header-section-number" > 7.2< / span > Aufgabenstellung
2< / h2 >
< p > In einem Bündner Ort beträgt der Mittelwert auf der Skala zur
sozialen Herkunft 5.6, er ist also genauso hoch wie in der
Gesamtschweiz. Was ist zur Lage dieses Wertes bezogen auf die Verteilung
in Graubünden zu sagen? Also: Wie viele Schüler in GR liegen mit ihrem
Wert darunter?< / p >
2022-11-18 21:10:07 +01:00
< pre class = "r" > < code > pnorm(5.6, mean = 5.1, sd = 2.0)< / code > < / pre >
2022-11-18 21:01:02 +01:00
< pre > < code > ## [1] 0.5987063< / code > < / pre >
< / div >
< / div >
2022-11-18 09:14:50 +01:00
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