The correct answer is:

both choices "A" and "B" are correct.

Explanation:

1. Hypothesis test for β = 0: This is a parametric test often used in linear regression. It assesses whether the slope of the regression line (β) is significantly different from zero, using a t-test or F-test.

2. ANOVA (Analysis of Variance): This is another parametric test used to compare means among multiple groups to determine if there is a statistically significant difference between them. ANOVA assumes normality of the data and homogeneity of variance.

Since both tests are parametric and test for statistical significance, the correct answer is both A and B are correct.

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Would you like further explanation or examples on parametric tests?

Related Questions:

1. What are the key assumptions underlying parametric tests?
2. How does a t-test differ from ANOVA in practical applications?
3. What is the role of the F-distribution in hypothesis testing?
4. Why are parametric tests preferred in certain scenarios over non-parametric tests?
5. How do you interpret p-values in hypothesis tests?

Tip:

Always verify the assumptions of normality and variance homogeneity before applying parametric tests to ensure the validity of your results.