{"id":206,"date":"2022-06-16T16:59:03","date_gmt":"2022-06-16T16:59:03","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/alphamodule\/?post_type=chapter&#038;p=206"},"modified":"2022-06-16T17:04:40","modified_gmt":"2022-06-16T17:04:40","slug":"data-collection-and-organization-apply-it-1","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/alphamodule\/chapter\/data-collection-and-organization-apply-it-1\/","title":{"raw":"Data Collection and Organization: Apply It 1","rendered":"Data Collection and Organization: Apply It 1"},"content":{"raw":"<div class=\"textbox learning-objectives\">\r\n<h3>Learning Goals<\/h3>\r\nDeepen your understanding and form connections within these skills:\r\n<ul>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Organize data in a spreadsheet.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Distinguish between observational units and variables in a dataset.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Distinguish between categorical and quantitative variables.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Distinguish between quantitative variables that are discrete or continuous.<\/li>\r\n \t<li aria-level=\"1\">Identify variables that can be used to collect data.<\/li>\r\n<\/ul>\r\n<\/div>\r\nIn\u00a0<em>What to Know [1C]<\/em>, you learned to distinguish between statistical investigative questions and survey questions. You also began to see that some data could be numerical or non-numerical. In this activity, we'll extend your understanding of statistical problem-solving by learning some key terms and organizational strategies associated with data collection.\r\n\r\nRecall the four steps of the statistical problem-solving process, from (1) forming a statistical question and (2) collecting data to (3) analyzing the data and (4) interpreting the results. Today we\u2019ll consider the connection between the first two steps. That is, how do we get from the statistical investigative question to a data collection plan? Along the way, you'll be able to see that there\u00a0are multiple data collection and organization strategies that may be considered for a single statistical question. You'll also consider ethical obligations related to data collection and storage.\r\n<h2>Data Collection and Organization<\/h2>\r\nIn practice, there are often multiple data collection options to consider. For example, if we were interested in the relationship between phone use in class and grades, there are many ways to define the relevant variables and collect and organize the information.\r\n\r\n<img class=\"wp-image-1064 aligncenter\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/5738\/2022\/01\/11231620\/Picture71-300x200.jpg\" alt=\"Several people sitting in a row all using their smartphones.\" width=\"726\" height=\"484\" \/>\r\n\r\nConsider Question 1 below individually, then compare your answer with a partner and discuss the similarities and differences in your answers.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 1<\/h3>\r\nDo you think there is a relationship between a student\u2019s phone use in class and their grades? Are there any details about \u201cphone use\u201d that are important to consider?\r\n\r\n[reveal-answer q=\"536624\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"536624\"]What do you think? Are there different ways to use a phone in class, some helpful, some not so helpful? [\/hidden-answer]\r\n\r\n<\/div>\r\n<h3>Data Organization<\/h3>\r\nA dataset contains information about a group of individuals or <strong>observational units<\/strong>. The characteristics of these observational units are recorded as <strong>variables<\/strong>. For example, the researcher collecting data on student phone use might ask individual students to report the number of times they checked their messages during class. In this case, the variable is the number of times messages were checked during class and the observational unit is one student response.\u00a0Prior to analyzing the data, it needs to be organized into a spreadsheet in rows and columns. See the example below for a demonstration.\r\n<div class=\"textbox exercises\">\r\n<h3>example<\/h3>\r\nPicture yourself as the researcher collecting responses for many survey questions (<strong>variables<\/strong>) from each individual (<strong>observational unit<\/strong>) you survey. The data will be organized into a spreadsheet, which consists of rows and columns. Naturally, there are only two possibilities for arranging the variable responses for each individual surveyed.\r\n\r\nWhich of the following two options do you think represents the way observational units and variables are usually organized in a spreadsheet?\r\n\r\nOption A: Each row is a variable and each column is an observational unit\r\n<table style=\"border-collapse: collapse; width: 99.7423%;\" border=\"1\">\r\n<tbody>\r\n<tr>\r\n<td style=\"width: 33.2907%;\">Variabiles<\/td>\r\n<td style=\"width: 33.2907%;\">Individual 1<\/td>\r\n<td style=\"width: 33.2907%;\">Individual 2<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 33.2907%;\">Variable 1<\/td>\r\n<td style=\"width: 33.2907%;\">response 1<\/td>\r\n<td style=\"width: 33.2907%;\">response 1<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 33.2907%;\">Variable 2<\/td>\r\n<td style=\"width: 33.2907%;\">response 2<\/td>\r\n<td style=\"width: 33.2907%;\">response 2<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 33.2907%;\">Variable 3<\/td>\r\n<td style=\"width: 33.2907%;\">response 3<\/td>\r\n<td style=\"width: 33.2907%;\">response 3<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nOption B: Each row is an observational unit and each column is a variable\r\n<table style=\"border-collapse: collapse; width: 100%;\" border=\"1\">\r\n<tbody>\r\n<tr>\r\n<td style=\"width: 183.891px;\">Individual surveyed<\/td>\r\n<td style=\"width: 183.891px;\">Variable 1<\/td>\r\n<td style=\"width: 183.891px;\">Variable 2<\/td>\r\n<td style=\"width: 183.922px;\">Variable\u00a0 3<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 183.891px;\">Individual 1<\/td>\r\n<td style=\"width: 183.891px;\">response 1<\/td>\r\n<td style=\"width: 183.891px;\">response 2<\/td>\r\n<td style=\"width: 183.922px;\">response 3<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"width: 183.891px;\">Individual 2<\/td>\r\n<td style=\"width: 183.891px;\">response 1<\/td>\r\n<td style=\"width: 183.891px;\">response 2<\/td>\r\n<td style=\"width: 183.922px;\">response 3<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n[reveal-answer q=\"251414\"]Show Answer[\/reveal-answer]\r\n[hidden-answer a=\"251414\"]If you haven't prepared spreadsheets for data collection before, it may not be obvious which of the two organization strategies is often preferred. Option B is the usual, recommended[footnote]<a href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00031305.2017.1375989\">https:\/\/www.biostat.wisc.edu\/~kbroman\/publications\/dataorg.pdf<\/a>[\/footnote] way to organize observational units and variables in a spreadsheet to make it easier to analyze.\u00a0 [\/hidden-answer]\r\n\r\n<span style=\"background-color: #ffff99;\">[The hidden answer includes a link to an open access article: Data Organization in Spreadsheets published in <em>The American Statistician<\/em>\u00a0and located at\u00a0 Taylor &amp; Francis Online. Please edit as needed in the preferred citation style.]<\/span>\r\n\r\n<\/div>\r\nAre you beginning to develop an image of how data can be organized in a spreadsheet? Answer Question 2 below to check your understanding.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 2<\/h3>\r\nA dataset contains information about a group of individuals or <strong>observational units<\/strong>. The characteristics of these observational units are recorded as <strong>variables<\/strong>. How are observational units and variables usually organized in a spreadsheet?\r\n\r\n[reveal-answer q=\"153850\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"153850\"]Put Answer Here[\/hidden-answer]\r\n\r\n<\/div>\r\n<h3>Types of Variables<\/h3>\r\nA variable is classified as <strong>categorical<\/strong> if it places an individual into one of several groups; it is classified as <strong>quantitative<\/strong> if it takes numerical values that can be used in arithmetic.\r\n\r\nThere are two types of quantitative variables. A <strong>discrete<\/strong> variable takes a fixed set of possible values, and it is not possible to get any value in between. In contrast, the range of outcomes for a <strong>continuous<\/strong> variable includes an infinite number of possible values. The discussion below provides a demonstration and examples of these types of variables. Try the question given in the Example before moving to Question 3.\r\n<div class=\"textbox exercises\">\r\n<h3>example<\/h3>\r\n<strong>Categorical Variables<\/strong>\r\n\r\nThese variables place an individual into one of several groups. Categorical survey questions are often encountered when completing forms that ask for information such as gender and race.\r\n\r\n<strong>Quantitative Variables<\/strong>\r\n\r\nQuantitative variables may be discrete or continuous.\r\n\r\n<strong>Discrete<\/strong> variables often require non-negative whole numbers as responses. For example, an automobile insurance applicant may be asked for how many accidents were they found to be at fault. Responses would necessarily be a whole number like [latex]0[\/latex],\u00a0[latex]1[\/latex], or\u00a0[latex]2[\/latex].\r\n\r\n<strong>Continuous<\/strong> variables take any number or fraction of a number as a response, such as weight in pounds ([latex]155[\/latex], [latex]187.2[\/latex], or [latex]221.9[\/latex]).\r\n\r\nEx. Imagine that you have been selected as a statistics intern in a veterinary clinic. The veterinarian wants to collect data about the dogs seen in her office. You've been asked to record information from the patient files to answer the survey questions listed below. For each, state whether the associated variable is categorical, discrete quantitative, or continuous quantitative and explain how you know.\r\n<ol>\r\n \t<li>What zip code does the dog's owner live in?<\/li>\r\n \t<li>What is the dog's weight in pounds?<\/li>\r\n \t<li>How many times has the dog been seen in the office?<\/li>\r\n \t<li>Does the owner have an outstanding balance due?<\/li>\r\n \t<li>How many pets are in the household in addition to the dog? ([latex]0[\/latex], [latex]1-2[\/latex], [latex]3-5[\/latex], more than [latex]5[\/latex])<\/li>\r\n<\/ol>\r\n[reveal-answer q=\"318506\"]Show Answer[\/reveal-answer]\r\n[hidden-answer a=\"318506\"]\r\n<ol>\r\n \t<li>Categorical; this question places individuals into one of a finite group of zip codes. If you thought this might be quantitative, note that it doesn't make sense to perform arithmetic on this variable (an average area code is meaningless!)<\/li>\r\n \t<li>Quantitative continuous:\u00a0weights may be recorded in fractions of a pound such as 60.0, 30.833, or 19.5. This response can also be restricted to weights rounded to the nearest whole pound, which would make it a discrete variable.<\/li>\r\n \t<li>Quantitative discreet: it would be impossible to have been seen 1.5 times.<\/li>\r\n \t<li>Categorical: this question requires one of two responses: yes, or no.<\/li>\r\n \t<li>Categorical: this may seem like a quantitative variable at first, but the response asks for one of four categories.<\/li>\r\n<\/ol>\r\n[\/hidden-answer]\r\n\r\n<\/div>\r\nNow you try identifying the types of variables present in survey questions with a partner. Work in pairs to discuss the list of survey questions given in Question 3.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 3<\/h3>\r\nConsider the survey questions below. If you used these questions to collect data, would the resulting variables be categorical or quantitative? For variables that are quantitative, classify them as discrete or continuous.\r\n\r\n&nbsp;\r\n\r\nWhat type of mobile phone do you have? (iPhone, Android, other)\r\n\r\n[reveal-answer q=\"242358\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"242358\"]Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.[\/hidden-answer]\r\n\r\n&nbsp;\r\n\r\nWhat is your area code?\r\n\r\n[reveal-answer q=\"980274\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"980274\"]Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.[\/hidden-answer]\r\n\r\n&nbsp;\r\n\r\nHow many devices capable of connecting to the Internet do you bring with you to class on a typical day?\r\n\r\n[reveal-answer q=\"638864\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"638864\"]Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.[\/hidden-answer]\r\n\r\n&nbsp;\r\n\r\nHow much time did you spend on your phone yesterday? (less than 2 hours, 2\u20135 hours, more than 5 hours)\r\n\r\n[reveal-answer q=\"574624\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"574624\"]Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.[\/hidden-answer]\r\n\r\n&nbsp;\r\n\r\nApproximately how much time do you spend on your phone in a typical day?\r\n\r\n[reveal-answer q=\"990667\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"990667\"]Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.[\/hidden-answer]\r\n\r\n&nbsp;\r\n\r\nDo you usually spend more time on your phone on weekdays or on weekends?\r\n\r\n[reveal-answer q=\"281623\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"281623\"]Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.[\/hidden-answer]\r\n\r\n<\/div>","rendered":"<div class=\"textbox learning-objectives\">\n<h3>Learning Goals<\/h3>\n<p>Deepen your understanding and form connections within these skills:<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Organize data in a spreadsheet.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Distinguish between observational units and variables in a dataset.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Distinguish between categorical and quantitative variables.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Distinguish between quantitative variables that are discrete or continuous.<\/li>\n<li aria-level=\"1\">Identify variables that can be used to collect data.<\/li>\n<\/ul>\n<\/div>\n<p>In\u00a0<em>What to Know [1C]<\/em>, you learned to distinguish between statistical investigative questions and survey questions. You also began to see that some data could be numerical or non-numerical. In this activity, we&#8217;ll extend your understanding of statistical problem-solving by learning some key terms and organizational strategies associated with data collection.<\/p>\n<p>Recall the four steps of the statistical problem-solving process, from (1) forming a statistical question and (2) collecting data to (3) analyzing the data and (4) interpreting the results. Today we\u2019ll consider the connection between the first two steps. That is, how do we get from the statistical investigative question to a data collection plan? Along the way, you&#8217;ll be able to see that there\u00a0are multiple data collection and organization strategies that may be considered for a single statistical question. You&#8217;ll also consider ethical obligations related to data collection and storage.<\/p>\n<h2>Data Collection and Organization<\/h2>\n<p>In practice, there are often multiple data collection options to consider. For example, if we were interested in the relationship between phone use in class and grades, there are many ways to define the relevant variables and collect and organize the information.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-1064 aligncenter\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/5738\/2022\/01\/11231620\/Picture71-300x200.jpg\" alt=\"Several people sitting in a row all using their smartphones.\" width=\"726\" height=\"484\" \/><\/p>\n<p>Consider Question 1 below individually, then compare your answer with a partner and discuss the similarities and differences in your answers.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Question 1<\/h3>\n<p>Do you think there is a relationship between a student\u2019s phone use in class and their grades? Are there any details about \u201cphone use\u201d that are important to consider?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q536624\">Hint<\/span><\/p>\n<div id=\"q536624\" class=\"hidden-answer\" style=\"display: none\">What do you think? Are there different ways to use a phone in class, some helpful, some not so helpful? <\/div>\n<\/div>\n<\/div>\n<h3>Data Organization<\/h3>\n<p>A dataset contains information about a group of individuals or <strong>observational units<\/strong>. The characteristics of these observational units are recorded as <strong>variables<\/strong>. For example, the researcher collecting data on student phone use might ask individual students to report the number of times they checked their messages during class. In this case, the variable is the number of times messages were checked during class and the observational unit is one student response.\u00a0Prior to analyzing the data, it needs to be organized into a spreadsheet in rows and columns. See the example below for a demonstration.<\/p>\n<div class=\"textbox exercises\">\n<h3>example<\/h3>\n<p>Picture yourself as the researcher collecting responses for many survey questions (<strong>variables<\/strong>) from each individual (<strong>observational unit<\/strong>) you survey. The data will be organized into a spreadsheet, which consists of rows and columns. Naturally, there are only two possibilities for arranging the variable responses for each individual surveyed.<\/p>\n<p>Which of the following two options do you think represents the way observational units and variables are usually organized in a spreadsheet?<\/p>\n<p>Option A: Each row is a variable and each column is an observational unit<\/p>\n<table style=\"border-collapse: collapse; width: 99.7423%;\">\n<tbody>\n<tr>\n<td style=\"width: 33.2907%;\">Variabiles<\/td>\n<td style=\"width: 33.2907%;\">Individual 1<\/td>\n<td style=\"width: 33.2907%;\">Individual 2<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.2907%;\">Variable 1<\/td>\n<td style=\"width: 33.2907%;\">response 1<\/td>\n<td style=\"width: 33.2907%;\">response 1<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.2907%;\">Variable 2<\/td>\n<td style=\"width: 33.2907%;\">response 2<\/td>\n<td style=\"width: 33.2907%;\">response 2<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 33.2907%;\">Variable 3<\/td>\n<td style=\"width: 33.2907%;\">response 3<\/td>\n<td style=\"width: 33.2907%;\">response 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Option B: Each row is an observational unit and each column is a variable<\/p>\n<table style=\"border-collapse: collapse; width: 100%;\">\n<tbody>\n<tr>\n<td style=\"width: 183.891px;\">Individual surveyed<\/td>\n<td style=\"width: 183.891px;\">Variable 1<\/td>\n<td style=\"width: 183.891px;\">Variable 2<\/td>\n<td style=\"width: 183.922px;\">Variable\u00a0 3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 183.891px;\">Individual 1<\/td>\n<td style=\"width: 183.891px;\">response 1<\/td>\n<td style=\"width: 183.891px;\">response 2<\/td>\n<td style=\"width: 183.922px;\">response 3<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 183.891px;\">Individual 2<\/td>\n<td style=\"width: 183.891px;\">response 1<\/td>\n<td style=\"width: 183.891px;\">response 2<\/td>\n<td style=\"width: 183.922px;\">response 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q251414\">Show Answer<\/span><\/p>\n<div id=\"q251414\" class=\"hidden-answer\" style=\"display: none\">If you haven&#8217;t prepared spreadsheets for data collection before, it may not be obvious which of the two organization strategies is often preferred. Option B is the usual, recommended<a class=\"footnote\" title=\"https:\/\/www.biostat.wisc.edu\/~kbroman\/publications\/dataorg.pdf\" id=\"return-footnote-206-1\" href=\"#footnote-206-1\" aria-label=\"Footnote 1\"><sup class=\"footnote\">[1]<\/sup><\/a> way to organize observational units and variables in a spreadsheet to make it easier to analyze.\u00a0 <\/div>\n<\/div>\n<p><span style=\"background-color: #ffff99;\">[The hidden answer includes a link to an open access article: Data Organization in Spreadsheets published in <em>The American Statistician<\/em>\u00a0and located at\u00a0 Taylor &amp; Francis Online. Please edit as needed in the preferred citation style.]<\/span><\/p>\n<\/div>\n<p>Are you beginning to develop an image of how data can be organized in a spreadsheet? Answer Question 2 below to check your understanding.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Question 2<\/h3>\n<p>A dataset contains information about a group of individuals or <strong>observational units<\/strong>. The characteristics of these observational units are recorded as <strong>variables<\/strong>. How are observational units and variables usually organized in a spreadsheet?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q153850\">Hint<\/span><\/p>\n<div id=\"q153850\" class=\"hidden-answer\" style=\"display: none\">Put Answer Here<\/div>\n<\/div>\n<\/div>\n<h3>Types of Variables<\/h3>\n<p>A variable is classified as <strong>categorical<\/strong> if it places an individual into one of several groups; it is classified as <strong>quantitative<\/strong> if it takes numerical values that can be used in arithmetic.<\/p>\n<p>There are two types of quantitative variables. A <strong>discrete<\/strong> variable takes a fixed set of possible values, and it is not possible to get any value in between. In contrast, the range of outcomes for a <strong>continuous<\/strong> variable includes an infinite number of possible values. The discussion below provides a demonstration and examples of these types of variables. Try the question given in the Example before moving to Question 3.<\/p>\n<div class=\"textbox exercises\">\n<h3>example<\/h3>\n<p><strong>Categorical Variables<\/strong><\/p>\n<p>These variables place an individual into one of several groups. Categorical survey questions are often encountered when completing forms that ask for information such as gender and race.<\/p>\n<p><strong>Quantitative Variables<\/strong><\/p>\n<p>Quantitative variables may be discrete or continuous.<\/p>\n<p><strong>Discrete<\/strong> variables often require non-negative whole numbers as responses. For example, an automobile insurance applicant may be asked for how many accidents were they found to be at fault. Responses would necessarily be a whole number like [latex]0[\/latex],\u00a0[latex]1[\/latex], or\u00a0[latex]2[\/latex].<\/p>\n<p><strong>Continuous<\/strong> variables take any number or fraction of a number as a response, such as weight in pounds ([latex]155[\/latex], [latex]187.2[\/latex], or [latex]221.9[\/latex]).<\/p>\n<p>Ex. Imagine that you have been selected as a statistics intern in a veterinary clinic. The veterinarian wants to collect data about the dogs seen in her office. You&#8217;ve been asked to record information from the patient files to answer the survey questions listed below. For each, state whether the associated variable is categorical, discrete quantitative, or continuous quantitative and explain how you know.<\/p>\n<ol>\n<li>What zip code does the dog&#8217;s owner live in?<\/li>\n<li>What is the dog&#8217;s weight in pounds?<\/li>\n<li>How many times has the dog been seen in the office?<\/li>\n<li>Does the owner have an outstanding balance due?<\/li>\n<li>How many pets are in the household in addition to the dog? ([latex]0[\/latex], [latex]1-2[\/latex], [latex]3-5[\/latex], more than [latex]5[\/latex])<\/li>\n<\/ol>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q318506\">Show Answer<\/span><\/p>\n<div id=\"q318506\" class=\"hidden-answer\" style=\"display: none\">\n<ol>\n<li>Categorical; this question places individuals into one of a finite group of zip codes. If you thought this might be quantitative, note that it doesn&#8217;t make sense to perform arithmetic on this variable (an average area code is meaningless!)<\/li>\n<li>Quantitative continuous:\u00a0weights may be recorded in fractions of a pound such as 60.0, 30.833, or 19.5. This response can also be restricted to weights rounded to the nearest whole pound, which would make it a discrete variable.<\/li>\n<li>Quantitative discreet: it would be impossible to have been seen 1.5 times.<\/li>\n<li>Categorical: this question requires one of two responses: yes, or no.<\/li>\n<li>Categorical: this may seem like a quantitative variable at first, but the response asks for one of four categories.<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n<p>Now you try identifying the types of variables present in survey questions with a partner. Work in pairs to discuss the list of survey questions given in Question 3.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>question 3<\/h3>\n<p>Consider the survey questions below. If you used these questions to collect data, would the resulting variables be categorical or quantitative? For variables that are quantitative, classify them as discrete or continuous.<\/p>\n<p>&nbsp;<\/p>\n<p>What type of mobile phone do you have? (iPhone, Android, other)<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q242358\">Hint<\/span><\/p>\n<div id=\"q242358\" class=\"hidden-answer\" style=\"display: none\">Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<p>What is your area code?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q980274\">Hint<\/span><\/p>\n<div id=\"q980274\" class=\"hidden-answer\" style=\"display: none\">Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<p>How many devices capable of connecting to the Internet do you bring with you to class on a typical day?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q638864\">Hint<\/span><\/p>\n<div id=\"q638864\" class=\"hidden-answer\" style=\"display: none\">Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<p>How much time did you spend on your phone yesterday? (less than 2 hours, 2\u20135 hours, more than 5 hours)<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q574624\">Hint<\/span><\/p>\n<div id=\"q574624\" class=\"hidden-answer\" style=\"display: none\">Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<p>Approximately how much time do you spend on your phone in a typical day?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q990667\">Hint<\/span><\/p>\n<div id=\"q990667\" class=\"hidden-answer\" style=\"display: none\">Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<p>Do you usually spend more time on your phone on weekdays or on weekends?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q281623\">Hint<\/span><\/p>\n<div id=\"q281623\" class=\"hidden-answer\" style=\"display: none\">Consider what type of answer this question could take: one of a list of options, a whole number, or a fraction of a number.<\/div>\n<\/div>\n<\/div>\n<hr class=\"before-footnotes clear\" \/><div class=\"footnotes\"><ol><li id=\"footnote-206-1\"><a href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00031305.2017.1375989\">https:\/\/www.biostat.wisc.edu\/~kbroman\/publications\/dataorg.pdf<\/a> <a href=\"#return-footnote-206-1\" class=\"return-footnote\" aria-label=\"Return to footnote 1\">&crarr;<\/a><\/li><\/ol><\/div>","protected":false},"author":17533,"menu_order":11,"template":"","meta":{"_candela_citation":"[]","CANDELA_OUTCOMES_GUID":"","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-206","chapter","type-chapter","status-publish","hentry"],"part":156,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/chapters\/206","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/wp\/v2\/users\/17533"}],"version-history":[{"count":4,"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/chapters\/206\/revisions"}],"predecessor-version":[{"id":212,"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/chapters\/206\/revisions\/212"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/parts\/156"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/chapters\/206\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/wp\/v2\/media?parent=206"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/pressbooks\/v2\/chapter-type?post=206"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/wp\/v2\/contributor?post=206"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/alphamodule\/wp-json\/wp\/v2\/license?post=206"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}