{"id":1574,"date":"2023-04-11T16:27:00","date_gmt":"2023-04-11T16:27:00","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/?post_type=chapter&#038;p=1574"},"modified":"2025-08-26T23:40:10","modified_gmt":"2025-08-26T23:40:10","slug":"representing-data-graphically-learn-it-1","status":"web-only","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/chapter\/representing-data-graphically-learn-it-1\/","title":{"raw":"Representing Data Graphically: Learn It 1","rendered":"Representing Data Graphically: Learn It 1"},"content":{"raw":"<section class=\"textbox learningGoals\">\r\n<ul>\r\n\t<li>Organize data using tables, charts, and graphs<\/li>\r\n\t<li>Create and analyze side-by-side and stacked bar graphs<\/li>\r\n\t<li>Create and analyze graphs of quantitative data<\/li>\r\n<\/ul>\r\n<\/section>\r\n<h2>Visualizing Data<\/h2>\r\n<p>Categorical, or qualitative, data are pieces of information that allow us to classify the objects under investigation into various categories. We usually begin working with categorical data by summarizing the data into a <strong>frequency table.<\/strong><\/p>\r\n<section class=\"textbox keyTakeaway\">\r\n<div>\r\n<h3>frequency table<\/h3>\r\n<p>A <strong>frequency table<\/strong> is a table with two columns. One column lists the categories, and another for the frequencies with which the items in the categories occur (how many items fit into each category).<\/p>\r\n<\/div>\r\n<\/section>\r\n<section class=\"textbox example\">An insurance company determines vehicle insurance premiums based on known risk factors. If a person is considered a higher risk, their premiums will be higher. One potential factor is the color of your car. The insurance company believes that people with some color cars are more likely to get in accidents. To research this, they examine police reports for recent total-loss collisions. The data is summarized in the frequency table below.\r\n\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td style=\"text-align: center;\"><strong>Color<\/strong><\/td>\r\n<td style=\"text-align: center;\"><strong>Frequency<\/strong><\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"text-align: center;\">Blue<\/td>\r\n<td style=\"text-align: center;\">[latex]25[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"text-align: center;\">Green<\/td>\r\n<td style=\"text-align: center;\">[latex]52[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"text-align: center;\">Red<\/td>\r\n<td style=\"text-align: center;\">[latex]41[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"text-align: center;\">White<\/td>\r\n<td style=\"text-align: center;\">[latex]36[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"text-align: center;\">Black<\/td>\r\n<td style=\"text-align: center;\">[latex]39[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td style=\"text-align: center;\">Grey<\/td>\r\n<td style=\"text-align: center;\">[latex]23[\/latex]<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]6906[\/ohm2_question]<\/section>\r\n<p>Sometimes we need an even more intuitive way of displaying data. This is where charts and graphs come in. There are many, many ways of displaying data graphically, but we will concentrate on one very useful type of graph called a <strong>bar graph<\/strong>.<\/p>\r\n<section class=\"textbox keyTakeaway\">\r\n<div>\r\n<h3>bar graph<\/h3>\r\n<p>A <strong>bar graph<\/strong> is a graph that displays a bar for each category with the length of each bar indicating the frequency of that category.<\/p>\r\n<p>&nbsp;<\/p>\r\n<\/div>\r\n<\/section>\r\n<p>To construct a bar graph, we need to draw a vertical axis and a horizontal axis. The vertical direction will have a scale and measure the frequency of each category; the horizontal axis has no scale in this instance.<\/p>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]738[\/ohm2_question]<\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]752[\/ohm2_question]<\/section>\r\n<section class=\"textbox example\">Using our car data from the insurance example at the top of the page, note the highest frequency is [latex]52[\/latex], so our vertical axis needs to go from [latex]0[\/latex] to [latex]52[\/latex], but we might as well use [latex]0[\/latex] to [latex]55[\/latex], so that we can put a hash mark every [latex]5[\/latex] units:<br \/>\r\n<center><img class=\"aligncenter wp-image-400\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175120\/vehiclecolor1.png\" alt=\"Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Blue (25), Green (53), Red (41), White (37), Black (39), Grey (24). \" width=\"350\" height=\"212\" \/><\/center><br \/>\r\nNotice that the height of each bar is determined by the frequency of the corresponding color.\u00a0 The horizontal gridlines are a nice touch, but\u00a0not necessary.\u00a0 In practice, you will find it useful to draw bar graphs using graph paper, so the gridlines will already be in place, or using technology.\u00a0 Instead of gridlines, we might also list the frequencies at the top of each bar, like this:<br \/>\r\n<center><img class=\"aligncenter wp-image-401\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175208\/vehiclecolor2.png\" alt=\"Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Blue (25), Green (52), Red (41), White (36), Black (39), Grey (23). \" width=\"350\" height=\"212\" \/><\/center><\/section>\r\n<p>In this case, our chart might benefit from being reordered from largest to smallest frequency values. This arrangement can make it easier to compare similar values in the chart, even without gridlines. When we arrange the categories in decreasing frequency order like this, it is called a <strong>Pareto chart<\/strong>.<\/p>\r\n<section class=\"textbox keyTakeaway\">\r\n<div>\r\n<h3>Pareto chart<\/h3>\r\n<p>A <strong>Pareto chart<\/strong> is a bar graph ordered from highest to lowest frequency.<\/p>\r\n<\/div>\r\n<\/section>\r\n<section class=\"textbox example\">Transforming our bar graph from earlier into a Pareto chart, we get:<center><img class=\"aligncenter wp-image-402\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175247\/vehiclecolor3.png\" alt=\"Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Green (52), Red (41), Black (39), White (36), Blue (25), Grey (23). \" width=\"350\" height=\"212\" \/><\/center><\/section>\r\n<p>A pie chart is an excellent visual tool for displaying the proportions of each category within a whole, with each 'slice' representing the relative size of a part, making it easier to see which categories are larger or smaller at a glance.<\/p>\r\n<section class=\"textbox keyTakeaway\">\r\n<div>\r\n<h3>pie chart<\/h3>\r\n<p>A <strong>pie chart<\/strong> is a circle with wedges cut of varying sizes marked out like slices of pie or pizza.\u00a0 The relative sizes of the wedges correspond to the relative frequencies of the categories. All pieces of a pie chart should add up to [latex]100\\%[\/latex].<\/p>\r\n<\/div>\r\n<\/section>\r\n<section class=\"textbox seeExample\">Create the pie chart for the following data regarding shark attacks in the U.S.\r\n\r\n<div align=\"center\">\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td><strong>U.S. State<\/strong><\/td>\r\n<td><strong>Count<\/strong><\/td>\r\n<td>\r\n<p><strong>Relative Frequency<\/strong><\/p>\r\n<p><strong>in Percent (%)<\/strong><\/p>\r\n<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>California<\/td>\r\n<td>[latex]33[\/latex]<\/td>\r\n<td>[latex]8.53[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Florida<\/td>\r\n<td>[latex]203[\/latex]<\/td>\r\n<td>[latex]52.45[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Hawaii<\/td>\r\n<td>[latex]51[\/latex]<\/td>\r\n<td>[latex]13.18[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>North Carolina<\/td>\r\n<td>[latex]23[\/latex]<\/td>\r\n<td>[latex]5.94[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Texas<\/td>\r\n<td>[latex]16[\/latex]<\/td>\r\n<td>[latex]4.13[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>South Carolina<\/td>\r\n<td>[latex]34[\/latex]<\/td>\r\n<td>[latex]8.79[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Other<\/td>\r\n<td>[latex]27[\/latex]<\/td>\r\n<td>[latex]6.98[\/latex]<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<p>[reveal-answer q=\"559876\"]Show Solution[\/reveal-answer]<br \/>\r\n[hidden-answer a=\"559876\"]<\/p>\r\n<center><img class=\"aligncenter wp-image-6699 size-full\" src=\"https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/10\/2022\/11\/16183530\/3.1.L.Pie_.png\" alt=\"Pie chart listing the states and shark attack percentages for US total. CA = 8.53%, FL = 52.45%, HI = 13.18%, NC = 5.94%, Other = 6.98%, SC = 8.79%, TX = 4.13%\" width=\"635\" height=\"543\" \/><\/center>\r\n<p>[\/hidden-answer]<\/p>\r\n<\/div>\r\n<\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]739[\/ohm2_question]<\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]758[\/ohm2_question]<\/section>\r\n<p>Pie charts look nice, but are harder to draw by hand than bar charts since to draw them accurately we would need to compute the angle each wedge cuts out of the circle, then measure the angle with a protractor. Computers are much better suited to drawing pie charts. Common software programs like Microsoft Word or Excel, OpenOffice.org, or Google Docs or Sheets are able to create bar graphs, pie charts, and other graph types. There are also numerous online tools that can create graphs.[footnote]For example: http:\/\/nces.ed.gov\/nceskids\/createAgraph[\/footnote]<\/p>\r\n<p><img class=\"wp-image-2132 alignleft\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images-archive-read-only\/wp-content\/uploads\/sites\/1468\/2016\/03\/22011815\/traffic-sign-160659.png\" alt=\"Caution\" width=\"75\" height=\"66\" \/>Don\u2019t get fancy with graphs! People sometimes add features to graphs that don\u2019t help to convey their information. For example, [latex]3[\/latex]-dimensional bar charts like the one shown below are usually not as effective as their two-dimensional counterparts.<\/p>\r\n<center>\r\n[caption id=\"attachment_407\" align=\"aligncenter\" width=\"350\"]<img class=\"wp-image-407\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175910\/carcolorbar.png\" alt=\"3D Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Blue (25), Green (52), Red (41), White (36), Grey (23), Black (39). The tilted angle of the display makes it difficult to line up the top of the bar with the frequency numbers.\" width=\"350\" height=\"211\" \/> Figure 1. A 3D graph[\/caption]\r\n<\/center>","rendered":"<section class=\"textbox learningGoals\">\n<ul>\n<li>Organize data using tables, charts, and graphs<\/li>\n<li>Create and analyze side-by-side and stacked bar graphs<\/li>\n<li>Create and analyze graphs of quantitative data<\/li>\n<\/ul>\n<\/section>\n<h2>Visualizing Data<\/h2>\n<p>Categorical, or qualitative, data are pieces of information that allow us to classify the objects under investigation into various categories. We usually begin working with categorical data by summarizing the data into a <strong>frequency table.<\/strong><\/p>\n<section class=\"textbox keyTakeaway\">\n<div>\n<h3>frequency table<\/h3>\n<p>A <strong>frequency table<\/strong> is a table with two columns. One column lists the categories, and another for the frequencies with which the items in the categories occur (how many items fit into each category).<\/p>\n<\/div>\n<\/section>\n<section class=\"textbox example\">An insurance company determines vehicle insurance premiums based on known risk factors. If a person is considered a higher risk, their premiums will be higher. One potential factor is the color of your car. The insurance company believes that people with some color cars are more likely to get in accidents. To research this, they examine police reports for recent total-loss collisions. The data is summarized in the frequency table below.<\/p>\n<table>\n<tbody>\n<tr>\n<td style=\"text-align: center;\"><strong>Color<\/strong><\/td>\n<td style=\"text-align: center;\"><strong>Frequency<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Blue<\/td>\n<td style=\"text-align: center;\">[latex]25[\/latex]<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Green<\/td>\n<td style=\"text-align: center;\">[latex]52[\/latex]<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Red<\/td>\n<td style=\"text-align: center;\">[latex]41[\/latex]<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">White<\/td>\n<td style=\"text-align: center;\">[latex]36[\/latex]<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Black<\/td>\n<td style=\"text-align: center;\">[latex]39[\/latex]<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Grey<\/td>\n<td style=\"text-align: center;\">[latex]23[\/latex]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm6906\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=6906&theme=lumen&iframe_resize_id=ohm6906&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n<p>Sometimes we need an even more intuitive way of displaying data. This is where charts and graphs come in. There are many, many ways of displaying data graphically, but we will concentrate on one very useful type of graph called a <strong>bar graph<\/strong>.<\/p>\n<section class=\"textbox keyTakeaway\">\n<div>\n<h3>bar graph<\/h3>\n<p>A <strong>bar graph<\/strong> is a graph that displays a bar for each category with the length of each bar indicating the frequency of that category.<\/p>\n<p>&nbsp;<\/p>\n<\/div>\n<\/section>\n<p>To construct a bar graph, we need to draw a vertical axis and a horizontal axis. The vertical direction will have a scale and measure the frequency of each category; the horizontal axis has no scale in this instance.<\/p>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm738\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=738&theme=lumen&iframe_resize_id=ohm738&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm752\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=752&theme=lumen&iframe_resize_id=ohm752&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n<section class=\"textbox example\">Using our car data from the insurance example at the top of the page, note the highest frequency is [latex]52[\/latex], so our vertical axis needs to go from [latex]0[\/latex] to [latex]52[\/latex], but we might as well use [latex]0[\/latex] to [latex]55[\/latex], so that we can put a hash mark every [latex]5[\/latex] units:<\/p>\n<div style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-400\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175120\/vehiclecolor1.png\" alt=\"Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Blue (25), Green (53), Red (41), White (37), Black (39), Grey (24).\" width=\"350\" height=\"212\" \/><\/div>\n<p>\nNotice that the height of each bar is determined by the frequency of the corresponding color.\u00a0 The horizontal gridlines are a nice touch, but\u00a0not necessary.\u00a0 In practice, you will find it useful to draw bar graphs using graph paper, so the gridlines will already be in place, or using technology.\u00a0 Instead of gridlines, we might also list the frequencies at the top of each bar, like this:<\/p>\n<div style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-401\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175208\/vehiclecolor2.png\" alt=\"Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Blue (25), Green (52), Red (41), White (36), Black (39), Grey (23).\" width=\"350\" height=\"212\" \/><\/div>\n<\/section>\n<p>In this case, our chart might benefit from being reordered from largest to smallest frequency values. This arrangement can make it easier to compare similar values in the chart, even without gridlines. When we arrange the categories in decreasing frequency order like this, it is called a <strong>Pareto chart<\/strong>.<\/p>\n<section class=\"textbox keyTakeaway\">\n<div>\n<h3>Pareto chart<\/h3>\n<p>A <strong>Pareto chart<\/strong> is a bar graph ordered from highest to lowest frequency.<\/p>\n<\/div>\n<\/section>\n<section class=\"textbox example\">Transforming our bar graph from earlier into a Pareto chart, we get:<\/p>\n<div style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-402\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175247\/vehiclecolor3.png\" alt=\"Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Green (52), Red (41), Black (39), White (36), Blue (25), Grey (23).\" width=\"350\" height=\"212\" \/><\/div>\n<\/section>\n<p>A pie chart is an excellent visual tool for displaying the proportions of each category within a whole, with each &#8216;slice&#8217; representing the relative size of a part, making it easier to see which categories are larger or smaller at a glance.<\/p>\n<section class=\"textbox keyTakeaway\">\n<div>\n<h3>pie chart<\/h3>\n<p>A <strong>pie chart<\/strong> is a circle with wedges cut of varying sizes marked out like slices of pie or pizza.\u00a0 The relative sizes of the wedges correspond to the relative frequencies of the categories. All pieces of a pie chart should add up to [latex]100\\%[\/latex].<\/p>\n<\/div>\n<\/section>\n<section class=\"textbox seeExample\">Create the pie chart for the following data regarding shark attacks in the U.S.<\/p>\n<div style=\"margin: auto;\">\n<table>\n<tbody>\n<tr>\n<td><strong>U.S. State<\/strong><\/td>\n<td><strong>Count<\/strong><\/td>\n<td>\n<p><strong>Relative Frequency<\/strong><\/p>\n<p><strong>in Percent (%)<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>California<\/td>\n<td>[latex]33[\/latex]<\/td>\n<td>[latex]8.53[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>Florida<\/td>\n<td>[latex]203[\/latex]<\/td>\n<td>[latex]52.45[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>Hawaii<\/td>\n<td>[latex]51[\/latex]<\/td>\n<td>[latex]13.18[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>North Carolina<\/td>\n<td>[latex]23[\/latex]<\/td>\n<td>[latex]5.94[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>Texas<\/td>\n<td>[latex]16[\/latex]<\/td>\n<td>[latex]4.13[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>South Carolina<\/td>\n<td>[latex]34[\/latex]<\/td>\n<td>[latex]8.79[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>Other<\/td>\n<td>[latex]27[\/latex]<\/td>\n<td>[latex]6.98[\/latex]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><div class=\"qa-wrapper\" style=\"display: block\"><button class=\"show-answer show-answer-button collapsed\" data-target=\"q559876\">Show Solution<\/button><\/p>\n<div id=\"q559876\" class=\"hidden-answer\" style=\"display: none\">\n<div style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-6699 size-full\" src=\"https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/10\/2022\/11\/16183530\/3.1.L.Pie_.png\" alt=\"Pie chart listing the states and shark attack percentages for US total. CA = 8.53%, FL = 52.45%, HI = 13.18%, NC = 5.94%, Other = 6.98%, SC = 8.79%, TX = 4.13%\" width=\"635\" height=\"543\" \/><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm739\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=739&theme=lumen&iframe_resize_id=ohm739&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm758\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=758&theme=lumen&iframe_resize_id=ohm758&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n<p>Pie charts look nice, but are harder to draw by hand than bar charts since to draw them accurately we would need to compute the angle each wedge cuts out of the circle, then measure the angle with a protractor. Computers are much better suited to drawing pie charts. Common software programs like Microsoft Word or Excel, OpenOffice.org, or Google Docs or Sheets are able to create bar graphs, pie charts, and other graph types. There are also numerous online tools that can create graphs.<a class=\"footnote\" title=\"For example: http:\/\/nces.ed.gov\/nceskids\/createAgraph\" id=\"return-footnote-1574-1\" href=\"#footnote-1574-1\" aria-label=\"Footnote 1\"><sup class=\"footnote\">[1]<\/sup><\/a><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-2132 alignleft\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images-archive-read-only\/wp-content\/uploads\/sites\/1468\/2016\/03\/22011815\/traffic-sign-160659.png\" alt=\"Caution\" width=\"75\" height=\"66\" \/>Don\u2019t get fancy with graphs! People sometimes add features to graphs that don\u2019t help to convey their information. For example, [latex]3[\/latex]-dimensional bar charts like the one shown below are usually not as effective as their two-dimensional counterparts.<\/p>\n<div style=\"text-align: center;\">\n<figure id=\"attachment_407\" aria-describedby=\"caption-attachment-407\" style=\"width: 350px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-407\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/276\/2016\/10\/12175910\/carcolorbar.png\" alt=\"3D Bar graph. Vertical measures Frequency, in increments of 5 from 0 to 55. Horizontal measures Vehicle color involved in a total-loss collision, showing from left Blue (25), Green (52), Red (41), White (36), Grey (23), Black (39). The tilted angle of the display makes it difficult to line up the top of the bar with the frequency numbers.\" width=\"350\" height=\"211\" \/><figcaption id=\"caption-attachment-407\" class=\"wp-caption-text\">Figure 1. A 3D graph<\/figcaption><\/figure>\n<\/div>\n<hr class=\"before-footnotes clear\" \/><div class=\"footnotes\"><ol><li id=\"footnote-1574-1\">For example: http:\/\/nces.ed.gov\/nceskids\/createAgraph <a href=\"#return-footnote-1574-1\" class=\"return-footnote\" aria-label=\"Return to footnote 1\">&crarr;<\/a><\/li><\/ol><\/div>","protected":false},"author":15,"menu_order":4,"template":"","meta":{"_candela_citation":"[]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":1572,"module-header":"learn_it","content_attributions":[],"internal_book_links":[],"video_content":null,"cc_video_embed_content":{"cc_scripts":"","media_targets":[]},"try_it_collection":null,"_links":{"self":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1574"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/users\/15"}],"version-history":[{"count":43,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1574\/revisions"}],"predecessor-version":[{"id":15700,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1574\/revisions\/15700"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/parts\/1572"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1574\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/media?parent=1574"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapter-type?post=1574"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/contributor?post=1574"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/license?post=1574"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}