{"id":19121,"date":"2016-02-22T09:30:40","date_gmt":"2016-02-22T17:30:40","guid":{"rendered":"http:\/\/www.questionpro.com\/?p=19121"},"modified":"2023-08-24T07:10:59","modified_gmt":"2023-08-24T07:10:59","slug":"data-analysis-101-ordinal","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/","title":{"rendered":"Data Analysis 101 &#8211; Ordinal"},"content":{"rendered":"\n<p>One could say there is a natural order to things. In survey research, when we think of order we are thinking about ordinal data. The ability to leverage the respondent\u2019s willingness to rank their choices is what differentiates ordinal from <a href=\"https:\/\/www.questionpro.com\/blog\/nominal-data\/\">nominal data<\/a>. This steps our analytical options up a notch from measuring simple percentages and modal values.<\/p>\n\n\n\n<p>Ordinal data is literally data that can be placed into order. This can be applied to baseball teams, horse racing, consumer preferences, or your place in the checkout line. A word of caution, <a class=\"wpil_keyword_link\" href=\"https:\/\/www.questionpro.com\/blog\/ordinal-data\/\"   title=\"ordinal data\" data-wpil-keyword-link=\"linked\"  data-wpil-monitor-id=\"165\">ordinal data<\/a> implies that we can specify an order, but we cannot speak accurately to the distance between those ordered items. The consistent distance between intervals is a function of <a href=\"https:\/\/www.questionpro.com\/blog\/interval-data\/\">interval data<\/a>, which will be covered in the next post.<\/p>\n\n\n\n<p>Asking participants to <a href=\"https:\/\/www.questionpro.com\/features\/rank-order.html\">rank-order<\/a> a series of companies, products or candidates is a common question type found in market research or political polling. For example:<\/p>\n\n\n\n\t<div class=\"banner-section wf-section\" lang=\"\" >\n\t\t<div class=\"right-column-container\">\n\t\t\t<div class=\"bannerbg white\">\n\t\t\t\t<span class=\"h1-2\">Create memorable experiences based on real-time data, insights and advanced analysis.<\/span>\n\t\t\t\t<a href=\"#userliteForm\" data-toggle=\"modal\" class=\"button w-button\">Request Demo<\/a>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t<div class=\"userlite-modal modal fade\" id=\"userliteForm\" tabindex=\"-1\" role=\"dialog\" style=\"display: none;\">\n\t\t<div class=\"modal-dialog\" role=\"document\">\n\t\t\t<div class=\"modal-content\" role=\"document\">\n\t\t\t\t<div class=\"modal-body\">\n\t\t\t\t\t<div class=\"modal-header\">\n\t\t\t\t\t\t<button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\">\n\t\t\t\t\t\t\t<i class=\"material-icons\">close<\/i>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"contact-us-form-wrapper contact-box\">\n\t\t\t\t\t\t<div class=\"userlite-form-wrapper\">\n\t\t\t\t\t\t\t<iframe src=\"https:\/\/www.questionpro.com\/userlite-form-blog-en.html?product=Research&amp;referralurl=https:\/\/www.questionpro.com\/blog\/wp-json\/wp\/v2\/posts\/19121&amp;lang=en&amp;cat=market-research\" style=\"display: block;\" ><\/iframe>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"demo-form-wrapper success-message-div\" style=\"display:none\">\n\t\t\t\t\t\t\t<p class=\"success-message-para\"><\/p>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\n\n\n<p>Please state your preference for the following candidates, with one (1) being least preferred and five (5) being most preferred.<\/p>\n\n\n\n<p>Donald Duck<br>Minnie Mouse<br>Bugs Bunny<br>Speed Racer<br>Buck Rogers<\/p>\n\n\n\n<p>As always your list should be randomized to prevent order bias. From the analysis standpoint, you can look at each contender\u2019s median rank accompanied by the percentage of times they were ranked most preferred. It would not be appropriate to use averages, as we cannot say with certainty the distance between one position and another is equal.<\/p>\n\n\n\n<p>The \u2018winner\u2019 or most preferred would be the brand that has the highest median rank (closest to five in this example). If you incorporate percentages in your analysis then you can say, for example, that twice as many respondents ranked Bugs Bunny as their most preferred candidate.<\/p>\n\n\n\n<p>Survey questions that work with ordinal data, such as the scenario above, force respondents to make a choice. As a <a href=\"https:\/\/www.questionpro.com\/blog\/surveys\/\">survey<\/a> author, you must decide whether or not to allow for ties (the same rank being applied to more than one category).<\/p>\n\n\n\n<p>Most multivariate statistical routines require continuous data, but there are routines that can work with ordinal data such as logistic <a href=\"https:\/\/www.questionpro.com\/blog\/regression-analysis\/\">regression analysis<\/a>. This technique allows you to incorporate multiple variables to predict an ordinal variable.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>One could say there is a natural order to things. In survey research, when we think of order we are [&hellip;]<\/p>\n","protected":false},"author":136,"featured_media":767433,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[203],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data Analysis 101 - Ordinal | QuestionPro<\/title>\n<meta name=\"description\" content=\"Ordinal data has numerous uses in market research specifically and survey research in general. 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It allows the respondent to provide an order of preference.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/\" \/>\n<meta property=\"og:site_name\" content=\"QuestionPro\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/questionpro\" \/>\n<meta property=\"article:published_time\" content=\"2016-02-22T17:30:40+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-08-24T07:10:59+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2016\/02\/bigstock-Business-People-Analysis-Think-116780105-800x534-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"800\" \/>\n\t<meta property=\"og:image:height\" content=\"534\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Greg Timpany\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@questionpro\" \/>\n<meta name=\"twitter:site\" content=\"@questionpro\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Greg Timpany\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/\"},\"author\":{\"name\":\"Greg Timpany\",\"@id\":\"https:\/\/www.questionpro.com\/blog\/#\/schema\/person\/dd964eb1605a56ae265b9c32f202ac62\"},\"headline\":\"Data Analysis 101 &#8211; Ordinal\",\"datePublished\":\"2016-02-22T17:30:40+00:00\",\"dateModified\":\"2023-08-24T07:10:59+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/\"},\"wordCount\":367,\"publisher\":{\"@id\":\"https:\/\/www.questionpro.com\/blog\/#organization\"},\"articleSection\":[\"Market Research\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/\",\"url\":\"https:\/\/www.questionpro.com\/blog\/data-analysis-101-ordinal\/\",\"name\":\"Data Analysis 101 - Ordinal | QuestionPro\",\"isPartOf\":{\"@id\":\"https:\/\/www.questionpro.com\/blog\/#website\"},\"datePublished\":\"2016-02-22T17:30:40+00:00\",\"dateModified\":\"2023-08-24T07:10:59+00:00\",\"description\":\"Ordinal data has numerous uses in market research specifically and survey research in general. 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