Final answer:
This question requires statistical hypothesis testing to determine significant associations with the target variable at a 5 percent level; this can be done using t-tests, F-tests, ANOVAs, or Z-tests, depending on the nature of the data and the comparison being performed.
Step-by-step explanation:
The question relates to statistical hypothesis testing at a 5 percent significance level. In statistics, determining whether variables are significantly associated with a target variable involves conducting hypothesis tests. Each of the given scenarios can be tested using appropriate statistical tests such as a t-test for mean comparison, a chi-square test for independence, an F-test for variance comparison, or others, depending on whether the data meets certain assumptions (e.g., normality, equal variances) and whether the standard deviations of the populations are known.
- Compare the effectiveness of two waxes with a t-test if variances are assumed equal or a Welch's t-test if not.
- Test the variation in waiting times using an F-test for variances if the assumption of normality is met.
- Determine if there's a statistical difference in mean playtime between boys and girls with a t-test.
- Assess the difference in GPA among teams with an ANOVA test if more than two groups are involved, or with a t-test if comparing two groups.
- Compare the ages of Democratic versus Republican senators using a t-test.
- Analyze the weighted alpha of stocks using a t-test or Z-test if the population standard deviations are known.
Each test requires setting up null and alternative hypotheses and calculating a test statistic that can be compared to critical values or used to calculate a p-value. If the p-value is less than 0.05, we reject the null hypothesis, indicating significant association at the 5 percent level.