In SPSS the researcher can specify the level of measurement as scale (numeric data on an interval or ratio scale), ordinal, or nominal. Nominal data deals with names, categories, or labels. The simplest measurement scale we can use to label variables is a nominal scale. Examples of nominal variables include region, zip code, or religious affiliation. A measurement such as 0 feet does make sense, as it represents no length.


Examples of scale variables include age in years, and income in thousands of Rupees, or score of a student in GRE exam. An overview of the annual average returns and market returns (2000-2005), Introduction to the Autoregressive Integrated Moving Average (ARIMA) model, The stakeholder theory of Corporate Social Responsibility, We are hiring freelance research consultants.

You can order things so that A is higher than a B, but without any other information, there is no way of knowing how much better an A is from a B. Nominal and ordinal data can be either string alphanumeric) or numeric but what is the difference? Nominal means "in name only" and that should help to remember what this level is all about. What is the difference between nominal, ordinal and scale?

Examples of ordinal variables include a degree of satisfaction among the consumers, preference degree from very high to very low, and degree of concern towards the certain issue.

The nominal value of a company's stock, or par value, is an arbitrary value assigned for balance sheet purposes when the company is … For example, for a string variable with the values of low, medium, high, the order of the categories is interpreted as high, low,medium which is not the correct order. Fill in your details below or click an icon to log in: You are commenting using your account. 2. If you use the assigned numerical value to calculate other figures like mean, median, etc. Nominal, ordinal and scale is a way to label data for analysis. Data at the interval level can be used in calculations. A complete waste of your time, since Social Security numbers are at the nominal level of measurement. Some data sets are continuous and some are discrete. Data at this level does not have a starting point. Nominal and ordinal data can be either string alphanumeric or numeric. The level of measurement you're working with will determine what it makes sense to do. Data at the nominal level is qualitative. However, 0 degrees (in both scales) cold as it may be does not represent the total absence of temperature. Our policy is that certified values for products should not deviate more than 1% from the nominal value (there are a few exceptions). We will look at each of these levels of measurement.​. Nominal. In SPSS, you can specify the level of measurement as scale (numeric data on an interval or ratio scale), ordinal, or nominal. The nominal level of measurement is the lowest of the four ways to characterize data. ( Log Out /  e.g. A Nominal Scale is a measurement scale, in which numbers serve as “tags” or “labels” only, to identify or classify an object. For example the department of the company in which an employee works. Even some things with numbers associated with them, such as a number on the back of a football jersey, are nominal since it is used to "name" an individual player on the field.

In general, it is more reliable to use numeric codes to represent ordinal data. Nominal Level of Measurement . Each of … In the primary research, a questionnaire contains questions pertaining to different variables. Data at the ratio level possess all of the features of the interval level, in addition to a zero value.

Examples of nominal variables include region, zip code, or gender of individual or religious affiliation.

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