A set of data is said to be nominal if the values / observations belonging to it can be assigned a code in the form of a number where the numbers are simply labels. You can count but not order or measure nominal data. For example, in a data set males could be coded as 0, females as 1; marital status of an individual could be coded as Y if married, N if single. (Source: stats.gla.ac.uk)
Certain statistical concepts are meaningless for nominal data. For example it would be silly to ask what are the mean and standard deviation are for race/ethnicity.
There are four types of data that may be gathered in social research, each one adding more to the next. Thus ordinal data is also nominal, and so on.
The name ‘Nominal’ comes from the Latin nomen, meaning ‘name’ and nominal data are items which are differentiated by a simple naming system. The only thing a nominal scale does is to say that items being measured have something in common, although this may not be described. Nominal items may have numbers assigned to them. This may appear ordinal but is not — these are used to simplify capture and referencing. Nominal items are usually categorical, in that they belong to a definable category, such as ‘employees’. (Source: changingminds.org)
Joshua is working to become a Data Scientist with focus on Analytics, Big Data, Machine Learning, and Statistics. His passion for Data and Information are second to none. He is a certified IBM Cognos Expert with more than 10 years experience in Business Intelligence & Data Warehousing, Analtyics, IT Management, Software Engineering and Supply Chain Performance Management with Fortune 500 companies. He has specializations in Analytics, Mobile Reporting, Performance Management, and Business Analysis.
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