Introduction There are four measurement scales, or types of data, nominal, ordinal interval and ratio. These four measurements are simple ways to categorize different types of variables. This paper will discuss the usage of each scale.
Nominal
Nominal scales are the most commonly used in marketing research. Nominal scales are used for labeling variables, without any quantitative value. In fact, Nominal scales could be called “labels”. Nominal are categories with numbers assigned to them to facilitate analysis. “A nominal scale partitions data into categories that are mutually exclusive and collectively exhaustive, implying that every bit of data will fit into one and only one category and that all data will fit somewhere on the scale.” (McDaniel, C. Jr., & G, R. (2007). Marketing Research (7th ed. p. 269) Nominal uses numerals to identify objects, individuals, events, or groups. This determines the equality or inequality of a situation. The classification that nominal falls under is male/female, buyer/non-buyer, etc. Most nominal data is collected via questions that provide the respondent a list of items to choose from.

Examples of Nominal Scales

Ordinal
“Ordinal scales have the labeling characteristics of nominal scales plus an ability to order data.” (McDaniel, C. Jr., & G, R. (2007). Marketing Research (7th ed. p. 270). With ordinal scales, it is the order of the values that is important and significant. In most cases, Ordinal scales are typically measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.
Samples of Ordinal Scales In the first example, it is easy to see that #4 would be better than #1 as far as happiness is concerned.
Another example of Ordinal Scale would be the grading system in schools. A’s are better than B’s and B’s are better than C’s and so forth, however; is A four times better than D? Is it two times better? In this case, the order is important but not the differences.
Interval
“Interval scales have the characteristics of ordinal scales, plus equal intervals between points to show relative amounts; they may include an arbitrary zero point.” (McDaniel, C. Jr., & G, R. (2007). Marketing Research) Interval scales provide information about order, and also possess equal intervals. From the previous example, if we knew that the distance between 1 and 2 was the same as that between 7 and 8 on our 10-point rating scale, then we would have an interval scale. An example of an interval scale is temperature, either measured on a Fahrenheit or Celsius scale. A degree represents the same underlying amount of heat, regardless of where it occurs on the scale. Measured in Fahrenheit units, the difference between a temperature of 46 and 42 is the same as the difference between 72 and 68. Equal-interval scales of measurement can be devised for opinions and attitudes. Constructing them involves an understanding of mathematical and statistical principles beyond those covered in this course. But it is important to understand the different levels of measurement when using and interpreting scales.

Ratio
In addition to possessing the qualities of nominal, ordinal, and interval scales, a ratio scale has an absolute zero (a point where none of the quality being measured exists). Using a ratio scale permits comparisons such as being twice as high, or one-half as much. Reaction time (how long it takes to respond to a signal of some sort) uses a ratio scale of measurement -- time. Although an individual's reaction time is always greater than zero, we conceptualize a zero point in time, and can state that a response of 24 milliseconds is twice as fast as a response time of 48 Milliseconds. Examples: RULER: inches or centimeters YEARS of work experience INCOME: money earned last year NUMBER of children

Conclusion It's important to recognize that there is a hierarchy implied in the level of measurement idea. At lower levels of measurement, assumptions tend to be less restrictive and data analyses tend to be less sensitive. At each level up the hierarchy, the current level includes all of the qualities of the one below it and adds something new. In general, it is desirable to have a higher level of measurement (e.g., interval or ratio) rather than a lower one (nominal or ordinal).