Which of the following tests is most suitable for studying the association between income level of mothers and their buying practices for infant wear?

Correct option is B

The Chi-square test is the most appropriate test for studying the association between income level (categorical variable) of mothers and their buying practices (categorical variable) for infant wear. This test is used to determine whether there is a significant relationship between two categorical variables in a dataset. Since both income level and buying practices are typically classified into groups (e.g., low, middle, high income; frequent, occasional, rare buyers), the Chi-square test for independence is the best statistical method for this analysis.
Information Booster:
· The Chi-square test is a non-parametric test, meaning it does not assume a normal distribution of data.
· It is used to examine relationships between nominal (categorical) variables in survey and observational studies.
· If the Chi-square value is significant, it indicates a strong association between income level and buying practices.
Additional Knowledge:
· T-test:
· Used to compare means between two groups (e.g., income level of working vs. non-working mothers).
· Not suitable for analyzing associations between two categorical variables.
· ANOVA:
· Used to compare means across multiple groups, such as comparing average spending on infant wear across different income groups.
· It is not used for testing associations between two categorical variables.
· Pearson's r:
· Measures the correlation between two continuous (numerical) variables.
· Since income level and buying practices are categorical, Pearson’s r is not appropriate.