{"id":26375,"date":"2021-08-19T04:54:34","date_gmt":"2021-08-19T04:54:34","guid":{"rendered":"https:\/\/analystprep.com\/cfa-level-1-exam\/?p=26375"},"modified":"2025-03-21T20:54:18","modified_gmt":"2025-03-21T20:54:18","slug":"selecting-data-visualizations-types","status":"publish","type":"post","link":"https:\/\/analystprep.com\/cfa-level-1-exam\/uncategorized\/selecting-data-visualizations-types\/","title":{"rendered":"Selecting Data Visualization Types"},"content":{"rendered":"<p><iframe loading=\"lazy\" src=\"\/\/www.youtube.com\/embed\/XCKuqfoNqOo\" width=\"611\" height=\"343\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<h2><strong>Guide to Selecting Visualization Types<\/strong><\/h2>\n<ul>\n<li>For numerical data, use a histogram, frequency polygon, or cumulative distribution chart.<\/li>\n<li>For category-based data, use a bar chart, tree-map, or heat map.<\/li>\n<li>For unstructured data, use a word cloud.<\/li>\n<li>For displaying relationships between two variables, use a scatter plot.<\/li>\n<li>For displaying relationships among more than two variables, use a scatter plot matrix or heat map.<\/li>\n<li>For displaying numerical data distributions, use a histogram, frequency polygon, or cumulative distribution chart.<\/li>\n<li>For displaying categorical data, use a bar chart, tree-map, or heat map.<\/li>\n<li>To draw a comparison over time, use a line chart for two variables and a bubble line chart for three.<\/li>\n<li>For drawing a comparison among categories, use a bar chart, tree-map, or heat map.<\/li>\n<\/ul>\n<h2><strong>Common Pitfalls<\/strong><\/h2>\n<p>The following are the four common pitfalls that we should avoid while using charts and graphs:<\/p>\n<ul>\n<li>Selecting the wrong chart type will occsion an inaccurate interpretation of data.<\/li>\n<li>Selectively plotting data could prove an inaccurate relationship.<\/li>\n<li>Data plotted in a truncated graph, e.g., having a y-axis that does not start at zero, could inaccurately show significant differences when there is really just a small difference.<\/li>\n<li>Scaling the axes incorrectly, for instance, by setting a maximum that is higher than necessary on the y-axis, can result in a graph that appears less steep and less volatile.<\/li>\n<\/ul>\n<blockquote>\n<h2><strong>Question<\/strong><\/h2>\n<p>Which of the following graphs is the <em>most appropriate<\/em> to use for plotting stock price change over a five-year period?<\/p>\n<ol style=\"list-style-type: upper-alpha;\">\n<li>Line chart.<\/li>\n<li>Bubble line chart.<\/li>\n<li>Frequency polygon.<\/li>\n<\/ol>\n<p><strong>Solution<\/strong><\/p>\n<p>The correct answer is <strong>A<\/strong>.<\/p>\n<p>A line chart is used to display the change of data series over time.<\/p>\n<p><strong>B is incorrect<\/strong>. In a bubble line chart, data points are represented by bubbles of varying sizes. The bubbles represent a third dimension of the data.<\/p>\n<p><strong>C is incorrect<\/strong>. The frequency polygon and the cumulative frequency distribution chart are also line charts. However, they represent data frequency distributions.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Guide to Selecting Visualization Types For numerical data, use a histogram, frequency polygon, or cumulative distribution chart. For category-based data, use a bar chart, tree-map, or heat map. For unstructured data, use a word cloud. 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