Which hypothesis test can you use to analyze paired sample data?

The paired t-test is specifically designed for analyzing paired sample data, making it the appropriate choice in this scenario. This statistical test is used when you have two related observations from the same group or individual. For example, it could be used to compare the measurements of a particular variable before and after a treatment or intervention.

In a paired t-test, the differences between each pair of observations are calculated, and then these differences are analyzed to determine if there is a statistically significant mean difference between these paired observations. This method accounts for the inherent correlation between the pairs, improving the testing's sensitivity and accuracy.

The other tests listed do not apply to paired sample data. The 2-proportion test is used for comparing proportions from two different independent groups, ANOVA is used when comparing means across three or more groups, and the Chi-Square test is used for assessing relationships between categorical variables rather than mean differences among paired samples. Thus, the paired t-test is the correct and most relevant choice for this type of data analysis.