Which concept describes analyzing data across two or more variables to observe relationships within a table?

Which concept describes analyzing data across two or more variables to observe relationships within a table?

• A. Cross-tabulation.
• B. Descriptive statistics.
• C. Regression analysis.
• D. Normalization.

Answer: (A)

Cross-tabulation analyzes data across two or more variables by organizing counts or percentages into a contingency table. Each cell shows the frequency or proportion for a specific combination of variable categories, making it easy to see whether different levels of one variable relate to levels of another. This table-based view of how variables interact is exactly what you’re looking for when you want to observe relationships within the data. Descriptive statistics summarize a single variable at a time, giving measures like mean or frequency without revealing how two variables relate. Regression analysis models the relationship between a dependent variable and one or more independent variables, often for prediction, rather than simply showing the presence of a relationship in a table. Normalization adjusts data scales for comparability, not the exploration of relationships between variables in a table.

Cross-tabulation analyzes data across two or more variables by organizing counts or percentages into a contingency table. Each cell shows the frequency or proportion for a specific combination of variable categories, making it easy to see whether different levels of one variable relate to levels of another. This table-based view of how variables interact is exactly what you’re looking for when you want to observe relationships within the data.

Descriptive statistics summarize a single variable at a time, giving measures like mean or frequency without revealing how two variables relate. Regression analysis models the relationship between a dependent variable and one or more independent variables, often for prediction, rather than simply showing the presence of a relationship in a table. Normalization adjusts data scales for comparability, not the exploration of relationships between variables in a table.