Question

we suspect that automobile insurance premiums (in dollars) may be steadily decreasing with the drivers driving experience (in years), so we choose a random sample of drivers who have similar automobile insurance coverage and collect data about their ages and insurance premiums. which of the following is the most appropriate statistical test to use to determine if insurance premiums are decreasing with the drivers driving experience? a. anova b. inference for regression c. matched pairs t - test d. chi - squared test for independence e. two - sample t - test

Explanation:

• ANOVA is used to compare means of three or more groups. Here, we are looking at a relationship between two variables (insurance premiums and driving experience), not comparing multiple group means.
• Inference for regression is appropriate when we want to study the relationship between a response variable (insurance premiums) and an explanatory variable (driving experience) to see if there is a linear trend (in this case, a decreasing trend).
• Matched - pairs t - test is used when we have paired data (e.g., before - and - after measurements on the same subjects). There is no such pairing in this problem.
• Chi - squared test for independence is used for categorical variables. Insurance premiums and driving experience are numerical (quantitative) variables.
• Two - sample t - test is used to compare means of two independent groups. Again, we are interested in a relationship between two variables, not comparing group means.

Answer:

B. Inference for regression