Read sections 10.2-10.6 of Research Methods in Business Studies, Ch. 10. Reply to the following post in 100 words or
more.

HR managers may benefit from understanding the differences between the four types of research data. Some data are not quantifiable and other type of data may be numerical or parametric. Simon (2005) writes the NOIR definitions in a self-explanatory way as follows:

Nominal (name only) data, or levels of measurement, are characterized by information that consists of names, labels, or categories only. These data cannot be arranged in an ordering scheme and are considered to be the lowest level of measurement. There is no criterion by which values can be identified as greater than or less than other values. Researches cannot, for example, average 12 Democrats and 15 Republicans and come up with 13.5 Independents. We can, however, determine ratios and percentages and compare the results to other groups.

Ordinal (or ranked) levels of measurement generate data that may be arranged in some order, but differences between data values either cannot be determined or are meaningless. For example, we can classify income as low, middle, or high to provide information about relative comparisons, but the degrees of differences are not available.

Interval level of measurement is similar to the ordinal level, with the additional property that you can determine meaningful amounts of differences between data. The level, however, often lacks an inherent starting point. For example, in comparing the annual mean temperatures of states, the value of “0 degrees” does not indicate no heat, and it would be incorrect to say that 40 degrees is half as warm as 80 degrees. Grade point averages (GPAs) are also considered interval levels of measuring knowledge. If someone has a 0.0 GPA this does not mean that they have no knowledge.

Ratio level of measurement is considered the highest level of measurement. It includes an inherent zero starting point and fractional values. As the name implies, ratios are meaningful for this type of measurement. The heights of children, distances traveled, waiting times, and the amount of gasoline consumed are ratio levels of measurement. A special form of ratio-level measurement is the binary (or dummy) variable of 1.0. This code represents the presence (1) or absence (0) of a certain characteristic (p. 72).

The different types of data dictate the type of analysis. An example of nominal data may be the different positions of an organization or applicant flow. Ordinal data may be data that may be ranked in some order such as employee behavior that meets standards, does not meet standards, or exceeds standards.

Simon, M. (2005). Dissertation & scholarly research: A practical guide to start & complete your dissertation, thesis, or formal research project. Debuque, IA: Kendall/Hunt Publishing Company.