2) A sample of \(n+6\) scores has a mean of \(\mathrm{x}=20\). If one person with a score of \(\mathrm{X}\) \(=15\) is removed from the sample, what will be the value for the new mean?

3) On an exam with \(\mu=82\), you obtain a score of \(X=87\).

1. What would you prefer that the exam distribution had \(\sigma=2\) or \(\sigma=10\) ? Explain.
2. If your score is \(X=75\), what would you prefer \(\sigma =10\) ? Explain.

4. Give a population of \(N=7\) and \(S S=217\),

1. Find \(\sigma\)
2. Find \(s\) for \(n=5\) and \(\mathrm{SS}=96\)

5. Give a mean of \(\bar{x}=20\) and \(s=2\), find the corresponding \(x\) values (to 2 decimal places) for the \(z\) -scores \(z=0.5, z=1.11\), and \(z=3.02\)

6. A trick coin has been weighted so that heads occur with a probability of \(p=\) \(3 / 5\) and \(\mathrm{p}\) (tails) \(=2 / 5\), If you toss this coin 35 times:

1. How man heads would you expect to get an average?
2. What is the probability of obtaining 25 heads or greater? (Consider using the normal approximation)

7. The population IQ scores forms a normal distribution with a mean of \(\mu = 100\) and a standard deviation of \(\sigma=15\). What is the probability of obtaining a sample man greater than \(\bar{x}=105\) for both \(n=9\) and \(n=36\) ?

8. A researcher is testing the hypothesis that Baby Wagner during play improves object recognition. A sample of \(n=36\) babies are tested, the overall number of correctly recognized objects score for the sample was \(\bar{x}=6\).

1. If the population averages without Baby Wagner is \(\mu =5\) with \(\sigma=4\), determine if the Baby Wagner users have significantly higher scores. Use \(x=0.05\) for a one-tailed test.
2. Determine the Cohen's \(d\) for the above, regardless of the test results.

Chapter 14 , #1

Use the gss.sav data file to answer the following questions:

1. Perform the appropriate analyses to test whether the average number of hours of * daily television viewing (variable tvhours) is the same for men and women. Write a short summary of your results, including appropriate charts to illustrate your findings. Be sure to look at the distribution of hours of television viewed separately for men and women.

1. Based on the results you observed, is it reasonable to conclude that in the population, men and women watch the same amount of television?

Chapter 14, #8

Use the salary.sav data file to answer the following questions:

8. Use the Select Cases facility to restrict the analysis to clerical workers only (variable jobcat equals 1).

1. Test the assertion that male and female clerical workers have the same average starting salaries. Summarize your findings.
2. You are \(95 \%\) confident that the true difference in average beginning salaries for male and female clerical workers is in what range?
3. How often would you expect to see a difference at least as large in absolute value as the one you observed if, in fact, male and female clerical workers have the same beginning salaries?
4. Evaluate how well your data meet the assumptions needed for a two-independent samples \(t\) test.

Chapter 14, #9

The bank claims that male clerical workers are paid more than female clerical workers because they have more formal education. Do the data support this assertion? Explain.

Chapter 13, #1

Use the gssft.sav data file to answer the following questions:

1. Use the Compute facility (discussed in Appendix B) to create a new variable that is the difference between a husband's and wife's hours worked last week (variables husbhr and wifehr).

1. Make a histogram of the difference. What should you look for in the histogram?
2. Make a \(Q-Q\) plot of the differences. How does the distribution differ from the normal distribution?
3. Do you think it's reasonable to believe that the distribution of mean differences is normal? Why? Perform a paired \(t\) test using the Paired-Samples T Test procedure. Write a brief summary of your results. Be sure to state your null and alternative hypotheses.
4. Run a one-sample \(t\) test on the difference variable. Compare your results to those from the paired \(t\) test. In what ways are the two tests different?

Chapter 13, #4

Use the siqss.sav data file to answer the following questions:

4. Consider the difference between the number of e-mails a person sends in a day and the number of e-mails he or she receives.

1. Compute a variable that is the difference between the number of e-mails a person sends (emsend) and the number of e-mails a person receives (emrec). Make a histogram. Describe the histogram. Are there outliers?
2. Test the null hypothesis that the average number of e-mails sent is equal to the average number of e-mails received. What do you conclude?
3. Use the Select Cases facility to remove outliers. Do your conclusions change?

Chapter 15, #1

Use the gss.sav data file to answer the following questions:

1. In the General Social Survey people classified themselves as being very happy, pretty happy, or not too happy (variable happy). Consider the relationship between happiness and age.

1. Compute basic descriptive statistics for each of the three happiness groups.
2. Make boxplots of age for the three groups.
3. Does the assumption of equal variances in the groups appear reasonable? The assumption of normality?

Chapter 15, #5

5. Fest whether Dole, Clinton, and Perot supporters (variable pres96) differ in average age and education. Summarize your findings.

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