Exam 8: Contingency Tables

In a positive relationship, small values of the column variable are associated with small values of the row variable, and large values of the column variable are often associated with large values of the row variable.

The placement of the variables in contingency tables depends on the nature of the relationship.

Row and column totals in contingency tables are called the grand totals.

Pivot tables show statistics of one or more continuous variables for one or more categorical variables in the data cells.

The direction of a relationship is easier to determine in large tables than in small ones.

Searching for practical relevance and presenting results may involve some decisions regarding ethics.

A negative relationship means that large values of one variable are associated with large values of the other variable and that small values of one variable are associated with small values of the other variable.

A layer variable is one that defines the subset of data used for subsequent data tables.

A contingency table expresses the relationship between two categorical variables.

The term data cell is commonly used to refer to table cells that show the counts or percentages based on the values of the two variables.

Bivariate statistics is the study of two or more variables.

A statistical relationship means that as one variable changes, so too does another.

Typically, the dependent variable is placed in the column in contingency tables.

Analysts should first determine what information they want to know, and then try to organize their contingency table to use column percentages to obtain that information.

The term pivot is derived from the handy property that row and column variables can be readily transposed.

Creating more data cells decreases the possibility that some cells have very few observations.