In a research study comparing the effectiveness of two reading instruction methods, which statistical procedure should be used to analyze the differences?

The t test is the appropriate statistical procedure to analyze the differences between two reading instruction methods because it is specifically designed to compare the means of two groups. In this context, the study is likely assessing how well each reading instruction method improves student performance, which typically involves measuring numerical outcomes, such as scores on a reading assessment.

The t test evaluates whether the differences in means between the two groups are statistically significant. This helps determine if one method of instruction results in significantly better outcomes compared to the other. When researchers have two independent samples (in this case, the two different reading instruction methods), a t test is the most straightforward method for comparing those groups.

While the other statistical methods mentioned serve different purposes, they are not suitable for this scenario. For instance, a chi-square test is used for categorical data to examine the association between variables, whereas correlation analysis measures the strength and direction of a relationship between two continuous variables without implying causation. Repeated measures ANOVA is suited for situations where the same subjects are measured multiple times under different conditions, which does not apply here if the study involves different groups for each instruction method. Thus, the t test is the best choice for this analysis.