Ask questions<\/strong><\/p>\n Watch for misleading or confusing charts<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n When viewing charts, pay attention to the following items, as they are susceptible to design choices that mislead readers. Here are three examples.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n Bar charts with an axis not including zero (0)-An axis without a zero can be misleading on a bar chart, as it can distort the scale of differences between categorical data.<\/em><\/span><\/p>\n Colour confusion-Color is an effective tool for drawing attention to or differentiating areas of data but can cause confusion if not used carefully. For example, we usually associate density in maps with a darker colour, but if the author reverses the colour range, that can be confusing, and even misleading.<\/em><\/span><\/p>\n Wrong chart type for the data-Not all chart types work for the selected dimensions and measures.\u00a0 <\/em><\/span><\/p>\n Charts are the most effective and readable when matched to the right data and purpose.<\/em><\/p>\n A well-designed chart should be easy to read and understand, and should not mislead. Here’s how to be an educated data consumer Know the elements of charts Ask questions Watch for misleading or confusing charts When viewing charts, pay attention to the following items, as they are susceptible to design choices that mislead readers. Here […]<\/p>\n","protected":false},"author":6541,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[41],"tags":[],"class_list":["post-29176","post","type-post","status-publish","format-standard","hentry","category-utm"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/posts\/29176","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/users\/6541"}],"replies":[{"embeddable":true,"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/comments?post=29176"}],"version-history":[{"count":1,"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/posts\/29176\/revisions"}],"predecessor-version":[{"id":29180,"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/posts\/29176\/revisions\/29180"}],"wp:attachment":[{"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/media?parent=29176"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/categories?post=29176"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/people.utm.my\/nurazaliah\/wp-json\/wp\/v2\/tags?post=29176"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/people.utm.my\/nurazaliah\/wp-content\/uploads\/sites\/616\/2020\/09\/graph3.jpg\")
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<\/a><\/p>\n\n
\nExamples: Stock price change over a five-year period or website page views during a month.<\/span><\/li>\n
\nExamples: Volume of shirts in different sizes, or per cent of spending by department.<\/span><\/li>\n
\nExamples: Segment analysis of the target market or sales leads by individual rep.<\/span><\/li>\n
\nExamples: The per cent of a market for different segments, or sales numbers in a region.<\/span><\/li>\n
\nExamples: Storage usage across computer machines, comparing fiscal budgets between years.<\/span><\/li>\n
\nExamples: Project timeline, duration of a machine\u2019s use, availability of players on a team.<\/span><\/li>\n
\nExamples: Sales quota assessment, performance spectrum (great\/good\/poor).<\/span><\/li>\n
\nExamples: Male versus the female likelihood of having lung cancer at different ages, or technology early adopters\u2019 and laggards\u2019 purchase patterns of smartphones.<\/span><\/li>\n
\nExamples: Number of customers by company size, student performance on an exam, frequency of a product<\/span><\/li>\n
\nExamples: Number of customers in different geographies.defect.<\/span><\/li>\n
\nUse a sensible base geography. Examples: Rates of internet-usage in certain geographies, house prices in different neighbourhoods.<\/span><\/li>\n
\nExamples: Understanding your data at a glance, seeing how data is skewed towards one end, identifying outliers in your data.<\/span><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"