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Testing Hypotheses. In Exercises 13–24, assume that a simple random sample has been and test the given claim. Unless specified by your instructor, use either the P-value method or the critical value method for testing hypotheses. Identify the null and alternative hypotheses, test statistic, P-value (or range of P-values), or critical value(s), and state the final conclusion that addresses the original claim.

Course Evaluations Data Set 17 “Course Evaluations” in Appendix B includes data from student evaluations of courses. The summary statistics are n = 93, x = 3.91, s = 0.53. Use a 0.05 significance level to test the claim that the population of student course evaluations has a mean equal to 4.00.

Short Answer

Expert verified

The hypotheses are as follows.

H0:μ=4.00H1:μ4.00

The test statistic is -1.638.

The critical values are ±1.986.

The null hypothesis is failed to be rejected.

There is enough evidence to support the claim that the population mean of the student’s course evaluation is equal to 4.

Step by step solution

01

Given information

The summarised data for the student evaluation of the courses is as follows.

n=93x¯=3.91s=0.53

The significance level is 0.05 to test the claim that the mean of the course evaluations by the students is equal to 4.00.

02

Check the requirements

The required conditions are verified as follows.

  1. The sample, satisfies the condition of a simple random sampling, as it iss randomly collected from the student’s evaluation about the course.
  2. The sample size of 93 is greater than 30. Thus, there is no need to check for normality of the sample, as the condition for the sample size is satisfied.

As the value of σis unknown, the t-test will be applied.

03

State the hypotheses 

The null hypothesis H0represents the population mean of the student’s course evaluation, which is equal to 4. The alternate hypothesisH1 represents the population mean of the student’s course evaluation, which is not equal to 4.

Let μbe the population mean of the student’s course evaluation.

State the null and alternate hypotheses as follows.

H0:μ=4.00H1:μ4.00

04

State the critical value

The degree of freedom is obtained by using the formula df=n-1, where .n=93 So,

df=93-1=92

The critical value can be obtained using the t-distribution table with 92 degrees of freedom and a significance level of 0.05 for a two-tailed test.

From the t-table, the value is obtained as 1.986t0.052 corresponding to row 92 and column 0.05 (two-tailed).

Thus, the critical values are ±1.986.

05

Compute the test statistic

Apply the t-test to compute the test statistic using the formula t=x¯-μsn.

Substitute the respective value in the above formula and simplify.

t=3.91-40.5393=-1.638

06

State the decision 

Reject the null hypothesis when the absolute value of the observed test statistic is greater than the critical value. Otherwise, fail to reject the null hypothesis.

In this case,

t=-1.638=1.638<1.9860t0.052

The absolute value of the observed test statistic is less than the critical value. This implies that the null hypothesis is failed to be rejected.

07

Conclusion

As the null hypothesis is failed to be rejected, it can be concluded that there is sufficient evidence to support the claim that the mean of the population of the student’s course evaluation is equal to 4.

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Most popular questions from this chapter

In Exercises 9–12, refer to the exercise identified. Make subjective estimates to decide whether results are significantly low or significantly high, then state a conclusion about the original claim. For example, if the claim is that a coin favours heads and sample results consist of 11 heads in 20 flips, conclude that there is not sufficient evidence to support the claim that the coin favours heads (because it is easy to get 11 heads in 20 flips by chance with a fair coin).

Exercise 8 “Pulse Rates”

In Exercises 9–12, refer to the exercise identified. Make subjective estimates to decide whether results are significantly low or significantly high, then state a conclusion about the original claim. For example, if the claim is that a coin favours heads and sample results consist of 11 heads in 20 flips, conclude that there is not sufficient evidence to support the claim that the coin favours heads (because it is easy to get 11 heads in 20 flips by chance with a fair coin).

Exercise 5 “Online Data”

P-Values. In Exercises 17–20, do the following:

a. Identify the hypothesis test as being two-tailed, left-tailed, or right-tailed.

b. Find the P-value. (See Figure 8-3 on page 364.)

c. Using a significance level of α = 0.05, should we reject H0or should we fail to reject H0?

The test statistic of z = 2.01 is obtained when testing the claim that p0.345.

Calculating Power Consider a hypothesis test of the claim that the Ericsson method of gender selection is effective in increasing the likelihood of having a baby girl, so that the claim is p>0.5. Assume that a significance level of α= 0.05 is used, and the sample is a simple random sample of size n = 64.

a. Assuming that the true population proportion is 0.65, find the power of the test, which is the probability of rejecting the null hypothesis when it is false. (Hint: With a 0.05 significance level, the critical value is z = 1.645, so any test statistic in the right tail of the accompanying top graph is in the rejection region where the claim is supported. Find the sample proportion in the top graph, and use it to find the power shown in the bottom graph.)

b. Explain why the green-shaded region of the bottom graph represents the power of the test.

Confidence interval Assume that we will use the sample data from Exercise 1 “Video Games” with a 0.05 significance level in a test of the claim that the population mean is greater than 90 sec. If we want to construct a confidence interval to be used for testing the claim, what confidence level should be used for the confidence interval? If the confidence interval is found to be 21.1 sec < μ< 191.4 sec, what should we conclude about the claim?

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