Bivariate analysis – Cross tabulations

Bivariate analysis is concerned with the analysis of two variables at a time in order to uncover whether or not the two variables are related.

Exploring relationships between variables means searching for evidence that the variation in one variable coincides with variation in another variable. A variety of techniques is available for examining relationships, but their use depends on the nature of the two variables being analyzed.

 

Contingency / Cross Tabulation Tables in Data Analysis

• Contingency tables are flexible methods for analyzing relationships between variables.
• They allow simultaneous analysis of two variables, examining relationships between them.
• They are often used to include percentages for easier interpretation.

• Table 14.4 examines the relationship between gender and reasons for visiting the gym.
• Percentages are calculated as a percentage of the total number in each column.
• The presumed independent variable is presented as the column variable and the presumed dependent variable as the rows variable.
• Contingency tables are used to search for patterns of association.
• Females are more likely to visit the gym for weight loss and relaxation, while men are more likely to build strength.