Question

1.) One tailed test or two tailed test?

You are performing a hypothesis test for the mean sample weight of your fellow Intro to Statistics students. For your null hypothesis , the hypothesized mean weight for the entire campus student body is 165. You have no reason to know for your alternative hypothesis whether the actual mean weight for the entire student campus body is more or less than 165. So you decide to make your alternative hypothesis as not equal to 165.

Which test should you use?

2.) One tailed test or two tailed test?

Separate scenario unconnected to the previous example: If possible, you would like to be able to show a difference between your sample mean and the hypothesized population mean at the 95% confidence level. If there were no other factors to consider (although, sadly, there usually are), which test should you use?

3.) Type I error or Type II error?

The mean sample score for your QC statistics students on the last exam was statistically significant at the 80% confidence level compared to the mean score on that exam for the entire campus population. Even so, you decide to change your confidence level from 80% to 95% and perform the test again. In so doing, you are increasing the chance of which type of error?

4.) Type I error or Type II error?

This is your alpha level. It describes the actual level of error or risk involved. Which type of error is this?

5.) You want to examine the relationship between the following two variables (with accompanying attributes) as indicated:

Age (years)    Region of country  

0-18   Northeast

19-34    Midwest

35-54 South

55+ West

Which statistical test between the options below would be the most appropriate, and why?  You must explain your answer.

a) T test

b) Pearson’s r

c) Chi square

6.) A sample of 125 campus students who responded to a questionnaire had a mean age of 22.0 and a standard deviation of 5.0. The mean hypothesized population age for all campus students is 25.0.

a)  Set up the hypothesis (one sample t test) for these data at the 95% confidence level. Be sure to include the null hypothesis and alternative hypothesis in your response.

b) Compute the t test statistic for these data.

c) Are you able to reject the null hypothesis, or are you unable to reject it?

d) Calculate the confidence interval for the true population mean at the 95% confidence level.

7.) For the identical scenario, now set your confidence level at 99%.

a) Are you able to reject the null hypothesis, or are you unable to reject it?

b) Calculate the confidence interval for the true population mean at the 99% confidence level.

Answer 1

1. Here hypothesis is vs

As alternative hypothesis have inequality sign it is two tailed test

2. Here claim is that there is difference between sample mean and the hypothesized population mean.

Hence it is two tailed test

3. Level of significance and Type I error are same

So increasing CI level will increase the chance of type I error

4. Level of significance and Type I error are same.

So Type 1 error