Levels of Measurement

Wikipedia, the on-line, free encyclopedia,says:

The level of measurement of a variable in mathematics and statistics is a classification that is used to describe the nature of information contained within numbers assigned to objects and, therefore, within the variable. The levels were proposed by Stanley Smith Stevens in his 1946 article On the theory of scales of measurement. According to Stevens' theory of scales, different mathematical operations on variables are possible, depending on the level at which a variable is measured. In the paper he states "Scales are possible in the first place only because there is a certain isomorphism between what we can do with the aspects of objects and the properties of the numeral series.

According to the classification scheme, in statistics the kinds of descriptive statistics and significance tests that are appropriate depend on the level of measurement of the variables concerned

Stevens proposed four levels of measurement: nominal (also categorical or discrete); ordinal; interval; [and] ratio.

There's a lot in the Wikipedia article. Read the whole thing and google "Levels of Measurement" for a lot more.

Social Research Methods.net points out that

First, knowing the level of measurement helps you decide how to interpret the data from that variable...Second, knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned. If a measure is nominal, then you know that you would never average the data values or do a t-test on the data.

Check this website out for statistical methods. It looks to be excellent.

This is important for entrepreneurs who wish to analyze data. You can only use certain kinds of measures for data which are on different scales. Statistics offer a powerful set of intellectual tools to help entrepreneurs understand their world and to analyze it.

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