{"id":58047,"date":"2018-06-08T06:27:30","date_gmt":"2018-06-08T13:27:30","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=58047"},"modified":"2023-08-07T11:05:46","modified_gmt":"2023-08-07T11:05:46","slug":"nominal-vs-ordinal-scale","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/nominal-vs-ordinal-scale\/","title":{"rendered":"Nominal vs Ordinal Scale: What is the Difference?"},"content":{"rendered":"\n<p><span style=\"font-weight: 400;\">Nominal Scale and Ordinal Scale are two of the four <\/span><a href=\"https:\/\/www.questionpro.com\/blog\/nominal-ordinal-interval-ratio\/\"><span style=\"font-weight: 400;\">variable measurement scales<\/span><\/a><span style=\"font-weight: 400;\">. Both these measurement scales have their significance in <\/span><a href=\"https:\/\/www.questionpro.com\/survey-templates\/\"><span style=\"font-weight: 400;\">surveys\/questionnaires<\/span><\/a><span style=\"font-weight: 400;\">, polls, and their subsequent <a href=\"https:\/\/www.questionpro.com\/blog\/statistical-analysis-methods\/\">statistical analysis<\/a>. The difference between Nominal and Ordinal scale has a great impact on <a href=\"https:\/\/www.questionpro.com\/market-research.html\">market research analysis<\/a> methods due to the details and information each of them has to offer.<\/span><\/p>\n\n\n\n<p class=\"has-text-align-center\"><em><strong>LEARN ABOUT:<\/strong> <a href=\"https:\/\/www.questionpro.com\/blog\/level-of-analysis\/\">Level of Analysis<\/a><\/em><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.questionpro.com\/blog\/nominal-scale\/\">Nominal Scale<\/a> is derived from the Latin word \u201cnomalis\u201d which denotes \u201crelated to names\u201d, is usually used to indicate categories. These categories have corresponding numbers allotted for analysis of collected data. For example, a person\u2019s gender, ethnicity, hair color etc. are considered to be data for a nominal scale.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.questionpro.com\/blog\/ordinal-scale\/\">Ordinal Scale<\/a>, on the other hand, involves arranging information in a specific order, i.e. in comparison to one another and \u201crank\u201d each parameter (variable). For example, after a customer shops from a retail outlet, he\/she is asked to fill out a kiosk survey: \u201cOn a scale of 1-5, how was your shopping experience?\u201d &#8211; <\/span><\/p>\n\n\n\n<ul>\n<li><span style=\"font-weight: 400;\">1 indicates extremely unsatisfactory, 2 is unsatisfactory, 3 is neutral, 4 is satisfactory and 5 indicates extremely satisfactory.<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\"> Here, the data collected will be on an ordinal scale as there is a rank associated with each of the answer options, i.e. 2 is lower than 4 and 4 is lower than 5. <\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">But, in the ordinal scale, it is not mandatory for the difference between 4 (satisfactory) and 2 (unsatisfactory) to be the same as the difference between 5 (extremely satisfactory) and 3 (neutral), as the number is not assigned for quantitative measurement but is purely for tagging purposes.<\/span><\/li>\n<\/ul>\n\n\n\n<p class=\"has-text-align-center\"><strong><em>LEARN ABOUT:<\/em><\/strong> <a href=\"https:\/\/www.questionpro.com\/blog\/perceived-value\/\">Perceived Value<\/a><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Every statistician should evaluate this difference precisely as the other two variable scales, i.e., <\/span><a href=\"https:\/\/www.questionpro.com\/blog\/interval-scale\/\"><span style=\"font-weight: 400;\">Interval <\/span><\/a><span style=\"font-weight: 400;\">and <\/span><a href=\"https:\/\/www.questionpro.com\/blog\/ratio-scale\/\"><span style=\"font-weight: 400;\">Ratio<\/span><\/a><span style=\"font-weight: 400;\"> are articulately calculated.&nbsp;<\/span>Before we go ahead with the discussion about Nominal vs Ordinal scales, here is a brief description of Nominal and Ordinal levels of measurement-<\/p>\n\n\n\n<p><b>Nominal Level of Measurement: <\/b><span style=\"font-weight: 400;\">In nominal level of measurement, variables are differentiated by their namings. These variables have no order or hierarchy associated with them. <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Numbers associated with the names are mere tags with no mathematical aspect linked to them. These variables are descriptive in nature. In terms of statistics,&nbsp;nominal scale is the easiest to understand and implement. These variables have minimum two divisions such as Male\/Female, Yes\/No.<\/span><\/p>\n\n\n\n<p class=\"has-text-align-center\"><strong><em>LEARN ABOUT:<\/em><\/strong> <a href=\"https:\/\/www.questionpro.com\/blog\/descriptive-analysis\/\">Descriptive Analysis<\/a><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">This scale has no numerical value, for example &#8211; gender, ethnicity, race etc.<\/span><\/p>\n\n\n\n<p class=\"has-text-align-center\"><strong>LEARN ABOUT:<\/strong> <a href=\"https:\/\/www.questionpro.com\/blog\/system-usability-scale\/\">System Usability Scale<\/a><\/p>\n\n\n\n<p><b>Ordinal Level of Measurement: <\/b><span style=\"font-weight: 400;\">In ordinal level of measurement, the order of variables is critical. The difference between these variables is not established and is not an integral aspect of this measurement scale. <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The variables are identified and described along with allotting a value to each of these identified variables. In <\/span><a href=\"https:\/\/www.questionpro.com\/market-research.html\"><span style=\"font-weight: 400;\">market research<\/span><\/a><span style=\"font-weight: 400;\">, ordinal scales are used to analyze relative perceptions, choices, and feedbacks, i.e., marketers can evaluate the degree of customer satisfaction or happiness, understand whether their newsletters should go out more often, etc. <\/span><\/p>\n\n\n\n<p>   We invite you to read:&nbsp;<a href=\"https:\/\/www.questionpro.com\/blog\/nominal-ordinal-interval-ratio\/\">The \u201cNominal Ordinal Interval Ratio\u201d Scales<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Nominal vs Ordinal Scales: Points of Difference<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">In any business, the knowledge of different measurement variables is a prerequisite as it allows owners to make well-informed and statistical decisions. Every measurement scale a unique degree of detail to offer, such as Nominal scale offers basic detail and Ratio offers maximum detail. <\/span><\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><b>Factors <\/b><\/td><td><b>Nominal Scale<\/b><\/td><td><b>Ordinal Scale<\/b><\/td><\/tr><tr><td><span style=\"font-weight: 400;\">Description<\/span><\/td><td><span style=\"font-weight: 400;\">The variables of this scale are differentiated by their nomenclature and none other factors. <\/span>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">There is no implied sequence in which variables exist in nominal scale<\/span><\/p>\n<\/td><td><span style=\"font-weight: 400;\">These variables have a naturally occurring order present between them yet the difference between variables is unknown. <\/span>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">The value of difference between two variables on this scale cannot be calculated. For instance, the order of size is small, medium, large, extra large. But Small \u2013 Medium \u2260 Large \u2013 Extra Large. <\/span><\/p>\n<\/td><\/tr><tr><td><span style=\"font-weight: 400;\">Degree of Quantitative Value<\/span><\/td><td><span style=\"font-weight: 400;\">There is no quantitative value associated with variables on this scale. Instead, it is a qualitative measurement scale.<\/span><\/td><td><span style=\"font-weight: 400;\">Quantitative values are linked to ordinal variables but arithmetic evaluation cannot be conducted on these variables.<\/span><\/td><\/tr><tr><td><span style=\"font-weight: 400; hyphens: none; word-wrap: normal;\">Key Differentiators<\/span><\/td><td> <ul> <li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">These variables cannot be ordered. <\/span><\/li> <li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The variables of this scale are distinct.<\/span><\/li> <li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.questionpro.com\/blog\/nominal-data\/\">Nominal data<\/a> is not quantifiable. <\/span><\/li> <\/ul> <\/td><td>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Numbers are assigned to the variables of this scale.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">No arithmetic calculation can be done on these variables.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The difference between variables cannot be calculated.<\/span><\/li>\n<\/ul>\n<\/td><\/tr><tr><td><span style=\"font-weight: 400;\">Examples<\/span><\/td><td>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Sex (Male, Female)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Marital Status (Married, Divorced, Unmarried, Widowed etc.)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Religion (Christian, Jew, Muslim) <\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Race (Red Indian, South-east Asian etc.)<\/span><\/li>\n<\/ul>\n<\/td><td>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Rank in a class test (first, second or third) <\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Customer satisfaction ratings (On a scale of 0-10)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Socio-economic status<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Customer satisfaction degrees (Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Education qualification<\/span><\/li>\n<\/ul>\n<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Nominal Scale and Ordinal Scale are two of the four variable measurement scales. Both these measurement scales have their significance [&hellip;]<\/p>\n","protected":false},"author":86,"featured_media":58048,"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>Nominal vs Ordinal Scale: What is the Difference? | QuestionPro<\/title>\n<meta name=\"description\" content=\"There is a significant difference between nominal and ordinal scale - and understanding this difference is key for getting the right research data. 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Nominal scale is used to name variables and Ordinal scale provides information about the order of the variables. Both these measurement scales have their significance in surveys\/questionnaires, polls, and their subsequent statistical analysis. 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