Chartered Financial Analyst (CFA) Practice Exam Level 2

What is the primary purpose of a T Test in regression analysis?

1. To test the significance of the entire regression model

2. To evaluate the individual contribution of each coefficient

3. To assess the overall variance in the dependent variable

4. To determine the correlation between independent variables

The correct answer is: To evaluate the individual contribution of each coefficient

The primary purpose of a T Test in regression analysis is to evaluate the individual contribution of each coefficient. In the context of regression, once the model is estimated, each regression coefficient is associated with a T statistic, which assesses whether the coefficient significantly differs from zero. This significance test indicates whether the independent variable corresponding to that coefficient has a meaningful impact on the dependent variable when controlling for the other variables in the model. By using the T Test, analysts can determine if the relationship represented by that specific coefficient is statistically significant, thereby highlighting the importance of individual predictors in explaining the variation in the dependent variable. This allows researchers and practitioners to identify which variables contribute meaningfully to the model and which do not, guiding decisions in model refinement and interpretation. Other options focus on broader aspects of regression analysis, such as testing the significance of the overall model or assessing the variance in the dependent variable. However, these do not specifically address the role of the T Test in analyzing individual parameters within the model.