What is the difference between categorical, ordinal and numerical variables Different types of data measure things (items/cases) differently

What is the difference between categorical, ordinal and numerical variables Different types of data measure things (items/cases) differently. In order to know which of the different statistical procedures to use to determine if two variables are related requires knowledge of how the two variables are measured. This brief article explains the differences in variable types.

Types of Variables

This brief article introduces a second dimension of variables; basically, what is the role of a specific variable in the cause/effect proposition. That is, which is the ‘causing’ variable and which is the ‘effect’?

Descriptive and Inferential Statistics

This article describes the basic difference between analyses that assess variables one at a time (univariate or descriptive analyses) and those that assess the relationships among variables (bi- or multivariate … inferential analyses). While both are useful, it is inferential analyses that can assist us in assessing cause-and-effect.

Testing Concomitant Variation (.docx)

This article describes the important tests used to statistically establish whether one variable has an impact on another. As you might guess from the previous readings, the particular test will be determined by the nature of both the independent and dependent variables.

P-Value Definition

As mentioned in the previous article, the P-value or ‘significance’ is used to determine how strong a claim is that one variable actually influences another. This brief article gives further clarification of the concept, as well as a useful example.

(Some) Statistics for Managers Who Think They Hate Statistics

This presentation provides a fairly in-depth exploration of the statistics that managers use. While you will not be quizzed or tested on this material, business administrators are expected to have a basic understanding of these concepts (in order to make effective decisions).