1. Which of the following is a major difference between a hypothesis test with a

Question

1. Which of the following is a major difference between a hypothesis test with a t statistic and the test with a z-score?

You must know the population standard deviation for the z-score but not for the t statistic.

You use the normal distribution table to find critical values for t but not for z.

You must know the population median for the z-score but not for the t statistic.

There are no major differences between a t-test and a z-score test.

2. The results of a one-sample t-test are reported as follows: t(29) = 1.75, p = .06. Based on this report:

a. Did the researchers accept or reject the null hypothesis?

b. How many people were in the sample (what was the n)?

3. In ANOVA, the F ratio is a ratio of:

the difference you see in the samples to the difference you'd expect to see due to sampling error.

All of the other options is correct.

variance between groups to variance within groups.

effect to error.

You must know the population standard deviation for the z-score but not for the t statistic.

You use the normal distribution table to find critical values for t but not for z.

You must know the population median for the z-score but not for the t statistic.

There are no major differences between a t-test and a z-score test.

Explanation / Answer

Here' the answer to the question. I've given out reasons as well. Please don't hesitate to give a "thumbs up" to the answer in case you're satisfied with it.

1. We use t instead of Z distribution, is when we don't know the population deviation.

So, a. is correct

2.

a. A p-value of .06 is more than .05 ( critical value). We fail not reject when pvalue is more than .05. So, we accept the null hypothesis

b. Degrees of freedom, df = 29, so, Sample size, n = df+1 =29+1 = 30

So, sample size is 30

3. The F-ratio is c. variance between groups to variance within groups.

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