Econ 210 Exam 3

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. The 95% confidence interval for the difference between the means of the two populations is 0 to 6.92 -2 to 2 -1.96 to 1.96 -0.92 to 6.92

-0.92 to 6.92

The following information was obtained from matched samples. Individual Method 1 Method 2 1 7 5 2 5 9 3 6 8 4 7 7 5 5 6 Refer to Exhibit 10-5. The null hypothesis tested is H0: md = 0. The test statistic for the difference between the two population means is 2 0 -1 -2

-1

Read the t statistic from the table of t distributions and circle the correct answer. A one-tailed test (lower tail), a sample size of 10 at a .10 level of significance; t = 1.383 -1.372 -1.383 -2.821

-1.383

Read the z statistics from the normal distribution table and circle the correct answer. A two-tailed test at a .0694 level of significance; z = -1.96 and 1.96 -1.48 and 1.48 -1.09 and 1.09 -0.86 and 0.86

-1.48 and 1.48

Read the z statistic from the normal distribution table and circle the correct answer. A one-tailed test (lower tail) at a .063 level of significance; z = -1.86 -1.53 -1.96 -1.645

-1.53

n = 16 H0: m ≥ 80 nar005-1.jpg = 75.607 Ha: m < 80 s = 8.246 Assume population is normally distributed. Refer to Exhibit 9-5. The test statistic equals -2.131 -0.53 0.53 2.131

-2.131

A statistics teacher wants to see if there is any difference in the abilities of students enrolled in statistics today and those enrolled five years ago. A sample of final examination scores from students enrolled today and from students enrolled five years ago was taken. You are given the following information. Refer to Exhibit 10-3. The test statistic for the difference between the two population means is -.47 -.65 -1.5 -3

-3

Refer to Exhibit 10-5. The 95% confidence interval for the difference between the two population means is -3.776 to 1.776 -2.776 to 2.776 -1.776 to 2.776 0 to 3.776

-3.776 to 1.776

The following information was obtained from independent random samples. Assume normally distributed populations with equal variances. Sample 1 Sample 2 Sample Mean 45 42 Sample Variance 85 90 Sample Size 10 12 Refer to Exhibit 10-4. The 95% confidence interval for the difference between the two population means is -5.372 to 11.372 -5 to 3 -4.86 to 10.86 -2.65 to 8.65

-5.372 to 11.372

A statistics teacher wants to see if there is any difference in the abilities of students enrolled in statistics today and those enrolled five years ago. A sample of final examination scores from students enrolled today and from students enrolled five years ago was taken. You are given the following information. Refer to Exhibit 10-3. The point estimate for the difference between the means of the two populations is 58.5 9 -9 -6

-6

A statistics teacher wants to see if there is any difference in the abilities of students enrolled in statistics today and those enrolled five years ago. A sample of final examination scores from students enrolled today and from students enrolled five years ago was taken. You are given the following information. Refer to Exhibit 10-3. The 95% confidence interval for the difference between the two population means is -9.92 to -2.08 -3.92 to 3.92 -13.84 to 1.84 -24.228 to 12.23

-9.92 to -2.08

A statistics teacher wants to see if there is any difference in the abilities of students enrolled in statistics today and those enrolled five years ago. A sample of final examination scores from students enrolled today and from students enrolled five years ago was taken. You are given the following information. Refer to Exhibit 10-3. The p-value for the difference between the two population means is .0014 .0027 .4986 .9972

.0027

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took these 100 customers to check out was 3.0 minutes. It is known that the standard deviation of the checkout time is one minute. Refer to Exhibit 8-2. With a .95 probability, the sample mean will provide a margin of error of 0.95 0.10 .196 1.96

.196

The sample size that guarantees all estimates of proportions will meet the margin of error requirements is computed using a planning value of p equal to .01 .50 .51 .99

.50

Refer to Exhibit 10-2. The null hypothesis to be tested is H0: md = 0. The test statistic is -1.96 1.96 0 1.645

0

The following information was obtained from matched samples. The daily production rates for a sample of workers before and after a training program are shown below. Refer to Exhibit 10-2. The point estimate for the difference between the means of the two populations is -1 -2 0 1

0

n order to determine whether or not there is a significant difference between the hourly wages of two companies, the following data have been accumulated. Company A Company B Sample size 80 60 Sample mean $16.75 $16.25 Population standard deviation $1.00 $0.95 Refer to Exhibit 10-8. The p-value is 0.0013 0.0026 0.0042 0.0084

0.0026

Refer to Exhibit 9-1. The p-value is 0.5107 0.0214 0.0107 2.1

0.0107

n = 36 H0: m ≤ 20 nar001-1.jpg = 24.6 Ha: m > 20 s = 12 Refer to Exhibit 9-1. The p-value is 0.5107 0.0214 0.0107 2.1

0.0107

A random sample of 100 people was taken. Eighty of the people in the sample favored Candidate A. We are interested in determining whether or not the proportion of the population in favor of Candidate A is significantly more than 75%. Refer to Exhibit 9-6. The p-value is 0.2112 0.05 0.025 0.0156

0.0156

n = 16 H0: m ≥ 80 nar005-1.jpg = 75.607 Ha: m < 80 s = 8.246 Assume population is normally distributed. Refer to Exhibit 9-5. The p-value is equal to -0.0166 0.0166 0.0332 0.9834

0.0166

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took the customers in the sample to check out was 3.1 minutes. The population standard deviation is known to be 0.5 minutes. We want to test to determine whether or not the mean waiting time of all customers is significantly more than 3 minutes. Refer to Exhibit 9-2. The p-value is 0.025 0.0456 0.05 0.0228

0.0228

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. The p-value is 0.0668 0.0334 1.336 1.96

0.0668

In order to estimate the difference between the average hourly wages of employees of two branches of a department store, the following data have been gathered. For this problem, the degrees of freedom are computed to be 36. Refer to Exhibit 10-7. A 95% interval estimate for the difference between the two population means is 0.078 to 1.922 1.922 to 2.078 1.09 to 4.078 1.078 to 2.922

0.078 to 1.922

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took these 100 customers to check out was 3.0 minutes. It is known that the standard deviation of the checkout time is one minute. Refer to Exhibit 8-2. The standard error of the mean equals 0.001 0.010 0.100 1.000

0.100

Refer to Exhibit 9-3. The p-value is equal to 0.1151 0.3849 0.2698 0.2302

0.1151

In order to estimate the average time spent on the computer terminals per student at a local university, data were collected from a sample of 81 business students over a one-week period. Assume the population standard deviation is 1.2 hours. Refer to Exhibit 8-1. The standard error of the mean is 7.5 0.014 0.160 0.133

0.133

In order to estimate the average time spent on the computer terminals per student at a local university, data were collected from a sample of 81 business students over a one-week period. Assume the population standard deviation is 1.2 hours. Refer to Exhibit 8-1. With a 0.95 probability, the margin of error is approximately 0.26 1.96 0.21

0.26

If an interval estimate is said to be constructed at the 90% confidence level, the confidence coefficient would be 0.1 0.95 0.9 0.05

0.9

If we want to provide a 95% confidence interval for the mean of a population, the confidence coefficient is 0.485 1.96 0.95 1.645

0.95

A local department store is studying the shopping habits of its customers. They think that the longer customers spend in the store the more they buy. Their study resulted in the following information regarding the amount of time women and men spent in a store. Women Men Mean 6 minutes 12 seconds 5 minutes 46 seconds Population Standard deviation 4 seconds 5 seconds Sample size 32 50 Refer to Exhibit 10-10. The point estimate for the standard deviation of the difference between the means of the two populations is 9 -1 -9 1

1

In order to estimate the difference between the average hourly wages of employees of two branches of a department store, the following data have been gathered. For this problem, the degrees of freedom are computed to be 36. Refer to Exhibit 10-7. A point estimate for the difference between the two sample means is 1 2 3 4

1

In order to estimate the difference between the average hourly wages of employees of two branches of a department store, the following data have been gathered. Downtown Store North Mall Store Sample size 25 20 Sample mean $15 $14 Sample standard deviation $2 $1 For this problem, the degrees of freedom are computed to be 36. Refer to Exhibit 10-7. A 95% interval estimate for the difference between the two population means is 0.078 to 1.922 1.922 to 2.078 1.09 to 4.078 1.078 to 2.922

1.09 to 4.078

Read the z statistic from the normal distribution table and circle the correct answer. A one-tailed test (upper tail) at a .123 level of significance; z = 1.54 1.96 1.645 1.16

1.16

Refer to Exhibit 9-3. The test statistic equals 0.1714 0.3849 -1.2 1.2

1.2

A random sample of 100 people was taken. Eighty of the people in the sample favored Candidate A. We are interested in determining whether or not the proportion of the population in favor of Candidate A is significantly more than 75%. Refer to Exhibit 9-6. The test statistic is 0.80 0.05 1.25 2.00

1.25

Read the t statistic from the table of t distributions and circle the correct answer. A two-tailed test, a sample of 20 at a .20 level of significance; t = 1.328 2.539 1.325 2.528

1.328

A random sample of 81 automobiles traveling on a section of an interstate showed an average speed of 60 mph. The distribution of speeds of all cars on this section of highway is normally distributed, with a standard deviation of 13.5 mph. Refer to Exhibit 8-3. The value to use for the standard error of the mean is 13.5 9 2.26 1.5

1.5

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. If you are interested in testing whether or not the average salary of males is significantly greater than that of females, the test statistic is 2.0 1.5 1.96 1.645

1.5

A random sample of 81 automobiles traveling on a section of an interstate showed an average speed of 60 mph. The distribution of speeds of all cars on this section of highway is normally distributed, with a standard deviation of 13.5 mph. Refer to Exhibit 8-3. If we are interested in determining an interval estimate for m at 86.9% confidence, the z value to use is 1.96 1.31 1.51 2.00

1.51

Read the t statistic from the table of t distributions and circle the correct answer. A one-tailed test (upper tail), a sample size of 18 at a .05 level of significance t = 2.12 1.734 -1.740 1.740

1.740

The management of a department store is interested in estimating the difference between the mean credit purchases of customers using the store's credit card versus those customers using a national major credit card. You are given the following information. Refer to Exhibit 10-6. A 95% confidence interval estimate for the difference between the average purchases of the customers using the two different credit cards is 49 to 64 11.68 to 18.32 125 to 140 8 to 10

11.68 to 18.32

In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 10-12. The mean square between treatments (MSTR) is 3.34 10.00 50.00 12.00

12.00 50.00

The management of a department store is interested in estimating the difference between the mean credit purchases of customers using the store's credit card versus those customers using a national major credit card. You are given the following information. Refer to Exhibit 10-6. A point estimate for the difference between the mean purchases of the users of the two credit cards is 2 18 265 15

15

A random sample of 144 observations has a mean of 20, a median of 21, and a mode of 22. The population standard deviation is known to equal 4.8. The 95.44% confidence interval for the population mean is 15.2 to 24.8 19.2 to 20.8 19.216 to 20.784 21.2 to 22.8

19.2 to 20.8

A statistics teacher wants to see if there is any difference in the abilities of students enrolled in statistics today and those enrolled five years ago. A sample of final examination scores from students enrolled today and from students enrolled five years ago was taken. You are given the following information. Refer to Exhibit 10-3. The standard error of mc045-1.jpg is 12.9 9.3 4 2

2

The following information was obtained from independent random samples. Assume normally distributed populations with equal variances. Refer to Exhibit 10-4. The point estimate for the difference between the means of the two populations is 0 2 3 15

2

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. The standard error for the difference between the two means is 4 7.46 4.24 2.0

2.0

A random sample of 16 students selected from the student body of a large university had an average age of 25 years. We want to determine if the average age of all the students at the university is significantly different from 24. Assume the distribution of the population of ages is normal with a standard deviation of 2 years. Refer to Exhibit 9-4. The test statistic is 1.96 2.00 1.645 0.05

2.00

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took the customers in the sample to check out was 3.1 minutes. The population standard deviation is known to be 0.5 minutes. We want to test to determine whether or not the mean waiting time of all customers is significantly more than 3 minutes. Refer to Exhibit 9-2. The test statistic is 1.96 1.64 2.00 0.056

2.00

The t value with a 95% confidence and 24 degrees of freedom is 1.711 2.064 2.492 2.069

2.064

The z value for a 97.8% confidence interval estimation is 2.02 1.96 2.00 2.29

2.29

n = 36 H0: m ≤ 20 nar001-1.jpg = 24.6 Ha: m > 20 s = 12 Refer to Exhibit 9-1. The test statistic equals 2.3 0.38 -2.3 -0.38

2.3

In order to determine whether or not there is a significant difference between the hourly wages of two companies, the following data have been accumulated. Company A Company B Sample size 80 60 Sample mean $16.75 $16.25 Population standard deviation $1.00 $0.95 Refer to Exhibit 10-8. The test statistic is 0.098 1.645 2.75 3.01

2.75

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took these 100 customers to check out was 3.0 minutes. It is known that the standard deviation of the checkout time is one minute. Refer to Exhibit 8-2. The 95% confidence interval for the average checkout time of all customers is 3 to 5 1.36 to 4.64 2.804 to 3.196 1.04 to 4.96

2.804 to 3.196

Part of an ANOVA table is shown below. Refer to Exhibit 10-13. The mean square within treatments (MSE) is 60 15 300 20

20

A local department store is studying the shopping habits of its customers. They think that the longer customers spend in the store the more they buy. Their study resulted in the following information regarding the amount of time women and men spent in a store. Women Men Mean 6 minutes 12 seconds 5 minutes 46 seconds Population Standard deviation 4 seconds 5 seconds Sample size 32 50 Refer to Exhibit 10-10. The 95% confidence interval for the difference between the two population means is 24.04 to 27.96 1.96 -1.96 to 1.96 -24.04 to 27.96

24.04 to 27.96

Part of an ANOVA table is shown below. Refer to Exhibit 10-13. The test statistic is 2.25 6 2.67 3

3

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. The point estimate of the difference between the means of the two populations is -28 3 4 4

3

The management of a department store is interested in estimating the difference between the mean credit purchases of customers using the store's credit card versus those customers using a national major credit card. You are given the following information. Refer to Exhibit 10-6. At 95% confidence, the margin of error is 1.694 3.32 1.96 15

3.32

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. At 95% confidence, the margin of error is 1.96 1.645 3.920 2.000

3.920

In a completely randomized design involving four treatments, the following information is provided. The overall mean (the grand mean) for all treatments is 40.0 37.3 48.0 37.0

37.3

The following information was obtained from independent random samples. Assume normally distributed populations with equal variances. Sample 1 Sample 2 Sample Mean 45 42 Sample Variance 85 90 Sample Size 10 12 Refer to Exhibit 10-4. The standard error of mc051-1.jpg is 3.0 4.0 8.372 19.48

4.0

In an analysis of variance problem if SST = 120 and SSTR = 80, then SSE is 200 40 80 120

40

The use of the normal probability distribution as an approximation of the sampling distribution of mc006-1.jpg is based on the condition that both np and n(1 - p) equal or exceed .05 5 10 30

5

A random sample of 81 automobiles traveling on a section of an interstate showed an average speed of 60 mph. The distribution of speeds of all cars on this section of highway is normally distributed, with a standard deviation of 13.5 mph. Refer to Exhibit 8-3. The 86.9% confidence interval for m is 46.500 to 73.500 57.735 to 62.265 59.131 to 60.869 50 to 70

57.735 to 62.265

Part of an ANOVA table is shown below. Refer to Exhibit 10-13. The mean square between treatments (MSTR) is 20 60 300 15

60

It is known that the variance of a population equals 1,936. A random sample of 121 has been taken from the population. There is a .95 probability that the sample mean will provide a margin of error of 7.84 or less 31.36 or less 344.96 or less 1,936 or less

7.84 or less

It is known that the population variance equals 484. With a 0.95 probability, the sample size that needs to be taken to estimate the population mean if the desired margin of error is 5 or less is 25 74 189 75

75

A sample of 26 elements from a normally distributed population is selected. The sample mean is 10 with a standard deviation of 4. The 95% confidence interval for m is 6.000 to 14.000 9.846 to 10.154 8.384 to 11.616 8.462 to 11.538

8.384 to 11.616

In order to estimate the average time spent on the computer terminals per student at a local university, data were collected from a sample of 81 business students over a one-week period. Assume the population standard deviation is 1.2 hours. Refer to Exhibit 8-1. If the sample mean is 9 hours, then the 95% confidence interval is approximately 7.04 to 110.96 hours 7.36 to 10.64 hours 7.80 to 10.20 hours 8.74 to 9.26 hours

8.74 to 9.26 hours

A bank manager wishes to estimate the average waiting time for customers in line for tellers. A random sample of 50 times is measured and the average waiting time is 5.7 minutes. The population standard deviation of waiting time is 2 minutes. Which Excel function would be used to construct a confidence interval estimate? CONFIDENCE.NORM NORM.INV T.INV INT

CONFIDENCE.NORM

An auto manufacturer wants to estimate the annual income of owners of a particular model of automobile. A random sample of 200 current owners is taken. The population standard deviation is known. Which Excel function would not be appropriate to use to construct a confidence interval estimate? NORM.S.INV COUNTIF AVERAGE STDEV.S

COUNTIF

A soft drink filling machine, when in perfect adjustment, fills the bottles with 12 ounces of soft drink. Any overfilling or underfilling results in the shutdown and readjustment of the machine. To determine whether or not the machine is properly adjusted, the correct set of hypotheses is H0: m < 12 Ha: m £ 12 H0: m £ 12 Ha: m > 12 H0: m ¹ 12 Ha: m = 12 H0: m = 12 Ha: m =/= 12

H0: m = 12 Ha: m =/= 12

The academic planner of a university thinks that at least 35% of the entire student body attends summer school. The correct set of hypotheses to test his belief is H0: p > 0.35 Ha: p >= 0.35 H0: p <= 0.35 Ha: p > 0.35 H0: p >= 0.35 Ha: p < 0.35 H0: p > 0.35 Ha: p <= 0.35

H0: p >= 0.35 Ha: p < 0.35

A random sample of 25 employees of a local company has been measured. A 95% confidence interval estimate for the mean systolic blood pressure for all company employees is 123 to 139. Which of the following statements is valid? 95% of the sample of employees has a systolic blood pressure between 123 and 139. If the sampling procedure were repeated many times, 95% of the resulting confidence intervals would contain the population mean systolic blood pressure. 95% of the population of employees has a systolic blood pressure between 123 and 139. If the sampling procedure were repeated many times, 95% of the sample means would be between 123 and 139.

If the sampling procedure were repeated many times, 95% of the resulting confidence intervals would contain the population mean systolic blood pressure.

The test statistic F is the ratio MSE/MST MSTR/MSE SSTR/SSE SSTR/SST

MSTR/MSE

A newspaper wants to estimate the proportion of Americans who will vote for Candidate A. A random sample of 1000 voters is taken. Of the 1000 respondents, 526 say that they will vote for Candidate A. Which Excel function would be used to construct a confidence interval estimate? NORM.S.INV NORM.INV T.INV INT

NORM.S.INV

The level of significance can be any negative value value value larger than 0.1 None of the answers is correct.

None of the answers is correct.

A meteorologist stated that the average temperature during July in Chattanooga was 80 degrees. A sample of 32 Julys was taken. The correct set of hypotheses is H0: m < 80 Ha: m £ 80 H0: m <= 80 Ha: m > 80 H0: m ¹ 80 Ha: m = 80 None of the other answers are correct.

None of the other answers are correct.

In hypothesis testing if the null hypothesis is rejected, no conclusions can be drawn from the test the alternative hypothesis must also be rejected the data must have been accumulated incorrectly None of the other answers are correct.

None of the other answers are correct.

Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 64 36 Sample Mean Salary (in $1,000) 44 41 Population Variance 128 72 Refer to Exhibit 10-1. At 95% confidence, the conclusion is the average salary of males is significantly greater than females average salary of males is significantly lower than females salaries of males and females are equal None of these alternatives is correct.

None of these alternatives is correct.

Which of the following is not a required assumption for the analysis of variance? The random variable of interest for each population has a normal probability distribution. The variance associated with the random variable must be the same for each population. At least 2 populations are under consideration. Populations have equal means.

Populations have equal means.

A statistics teacher wants to see if there is any difference in the abilities of students enrolled in statistics today and those enrolled five years ago. A sample of final examination scores from students enrolled today and from students enrolled five years ago was taken. You are given the following information. Refer to Exhibit 10-3. What is the conclusion that can be reached about the difference in the average final examination scores between the two classes? (Use a .05 level of significance.) There is a statistically significant difference in the average final examination scores between the two classes. There is no statistically significant difference in the average final examination scores between the two classes. It is impossible to make a decision on the basis of the information given. There is a difference, but it is not significant.

There is a statistically significant difference in the average final examination scores between the two classes.

If a hypothesis test leads to the rejection of the null hypothesis, a Type II error must have been committed Type II error may have been committed Type I error must have been committed Type I error may have been committed

Type I error may have been committed

The error of rejecting a true null hypothesis is a Type I error a Type II error can be either a or b, depending on the situation committed when not enough information is available

a Type I error

An interval estimate is used to estimate the shape of the population's distribution the sampling distribution a sample statistic a population parameter

a population parameter

A Type I error is committed when a true alternative hypothesis is not accepted a true null hypothesis is rejected the critical value is greater than the value of the test statistic sample data contradict the null hypothesis

a true alternative hypothesis is not accepted

A Type II error is committed when a true alternative hypothesis is mistakenly rejected a true null hypothesis is mistakenly rejected the sample size has been too small not enough information has been available

a true null hypothesis is mistakenly rejected

As a general guideline, the research hypothesis should be stated as the null hypothesis alternative hypothesis tentative assumption hypothesis the researcher wants to disprove

alternative hypothesis

If we are interested in testing whether the mean of population 1 is significantly larger than the mean of population 2, the null hypothesis should state m1 - m2 > 0 null hypothesis should state m1 - m2 ³ 0 alternative hypothesis should state m1 - m2 > 0 alternative hypothesis should state m1 - m2 < 0

alternative hypothesis should state m1 - m2 > 0

Exhibit 9-1 n = 36 H0: m ≤ 20 nar001-1.jpg = 24.6 Ha: m > 20 s = 12 Refer to Exhibit 9-1. If the test is done at a .05 level of significance, the null hypothesis should not be rejected be rejected Not enough information is given to answer this question. None of the other answers are correct.

be rejected

Refer to Exhibit 9-1. If the test is done at a .05 level of significance, the null hypothesis should not be rejected be rejected Not enough information is given to answer this question. None of the other answers are correct.

be rejected

A random sample of 81 automobiles traveling on a section of an interstate showed an average speed of 60 mph. The distribution of speeds of all cars on this section of highway is normally distributed, with a standard deviation of 13.5 mph. Refer to Exhibit 8-3. If the sample size was 25 (other factors remain unchanged), the interval for m would not change become narrower become wider become zero

become wider

A 95% confidence interval for a population mean is determined to be 100 to 120. If the confidence coefficient is reduced to 0.90, the interval for m becomes narrower becomes wider does not change becomes 0.1

becomes narrower

Using an a = 0.04, a confidence interval for a population proportion is determined to be 0.65 to 0.75. If the level of significance is decreased, the interval for the population proportion becomes narrower becomes wider does not change Not enough information is provided to answer this question.

becomes wider

For a two-tailed test with a sample size of 40, the null hypothesis will not be rejected at a 5% level of significance if the test statistic is between -1.96 and 1.96, exclusively greater than 1.96 less than 1.645 greater than -1.645

between -1.96 and 1.96, exclusively

Part of an ANOVA table is shown below. Refer to Exhibit 10-13. If at 95% confidence, we want to determine whether or not the means of the populations are equal, the p-value is between 0.01 and 0.025 between 0.025 and 0.05 between 0.05 and 0.1 greater than 0.1

between 0.05 and 0.1

If two independent large samples are taken from two populations, the sampling distribution of the difference between the two sample means can be approximated by a Poisson distribution will have a variance of one can be approximated by a normal distribution will have a mean of one

can be approximated by a normal distribution

For a two-tailed hypothesis test about m, we can use any of the following approaches except compare the confidence interval estimate of m to the hypothesized value of m compare the p-value to the value of a compare the value of the test statistic to the critical value compare the level of significance to the confidence coefficient

compare the level of significance to the confidence coefficient

The probability that the interval estimation procedure will generate an interval that does not contain the actual value of the population parameter being estimated is the level of significance confidence level confidence coefficient error factor

confidence coefficient

The ability of an interval estimate to contain the value of the population parameter is described by the confidence level degrees of freedom precise value of the population mean m None of the other answers are correct.

confidence level

The confidence associated with an interval estimate is called the level of significance degree of association confidence level precision

confidence level

As the sample size increases, the margin of error increases decreases stays the same None of the other answers are correct.

decreases

The t distribution is a family of similar probability distributions, with each individual distribution depending on a parameter known as the finite correction factor sample size degrees of freedom standard deviation

degrees of freedom

To compute the minimum sample size for an interval estimate of m, we must first determine all of the following except desired margin of error confidence level population standard deviation degrees of freedom

degrees of freedom

For a two-tailed hypothesis test about a population mean, the null hypothesis can be rejected if the confidence interval is symmetric is non-symmetric includes m0 does not include m0

does not include m0

In order to determine whether or not the means of two populations are equal, a t test must be performed an analysis of variance must be performed either a t test or an analysis of variance can be performed a chi-square test must be performed

either a t test or an analysis of variance can be performed

For a one-tailed test (upper tail) with a sample size of 900, the null hypothesis will be rejected at the .05 level of significance if the test statistic is less than or equal to -1.645 greater than or equal to 1.645 less than 1.645 less than -1.96

greater than or equal to 1.645

A two-tailed test is a hypothesis test in which rejection region is in both tails of the sampling distribution hypothesis test in which rejection region is in one tail of the sampling distribution hypothesis test in which rejection region is only in the lower tail of the sampling distribution hypothesis test in which rejection region is only in the upper tail of the sampling distribution

hypothesis test in which rejection region is in both tails of the sampling distribution

A one-tailed test is a hypothesis test in which rejection region is in both tails of the sampling distribution hypothesis test in which rejection region is in one tail of the sampling distribution hypothesis test in which rejection region is only in the lower tail of the sampling distribution hypothesis test in which rejection region is only in the upper tail of the sampling distribution

hypothesis test in which rejection region is in one tail of the sampling distribution

An example of statistical inference is a population mean descriptive statistics calculating the size of a sample hypothesis testing

hypothesis testing

If a hypothesis test has a Type I error probability of .05, that means if the null hypothesis is false, it will not be rejected 5% of the time if the null hypothesis is false, it will be rejected 5% of the time if the null hypothesis is true, it will not be rejected 5% of the time if the null hypothesis is true, it will be rejected 5% of the time

if the null hypothesis is true, it will be rejected 5% of the time

In testing for the equality of k population means, the number of treatments is k k - 1 nT nT - k

k

In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided. SSTR = 200 (Sum Square Between Treatments) SST = 800 (Total Sum Square) Refer to Exhibit 10-12. If at 95% confidence we want to determine whether or not the means of the five populations are equal, the p-value is between 0.05 and 0.10 between 0.025 and 0.05 between 0.01 and 0.025 less than 0.01

less than 0.01

If the cost of a Type I error is high, a smaller value should be chosen for the critical value confidence coefficient level of significance test statistic

level of significance

When each data value in one sample is matched with a corresponding data value in another sample, the samples are known as corresponding samples matched samples independent samples None of these alternatives is correct.

matched samples

If a hypothesis is rejected at a 5% level of significance, it will always be rejected at the 1% level will always be accepted at the 1% level will never be tested at the 1% level may be rejected or not rejected at the 1% level

may be rejected or not rejected at the 1% level

The within-treatments estimate of s 2 is called the sum of squares due to error mean square due to error sum of squares due to treatments mean square due to treatments

mean square due to error

As the degrees of freedom increase, the t distribution approaches the uniform distribution normal distribution exponential distribution p distribution

normal distribution

Refer to Exhibit 9-3. If the test is done at a 5% level of significance, the null hypothesis should not be rejected be rejected Not enough information given to answer this question. None of the other answers are correct.

not be rejected

n = 16 H0: m ≥ 80 nar005-1.jpg = 75.607 Ha: m < 80 s = 8.246 Assume population is normally distributed. Refer to Exhibit 9-5. If the test is done at a 2% level of significance, the null hypothesis should not be rejected be rejected Not enough information is given to answer this question. None of the other answers are correct.

not be rejected

Exhibit 9-4 A random sample of 16 students selected from the student body of a large university had an average age of 25 years. We want to determine if the average age of all the students at the university is significantly different from 24. Assume the distribution of the population of ages is normal with a standard deviation of 2 years. Refer to Exhibit 9-4. At a .05 level of significance, it can be concluded that the mean age is not significantly different from 24 significantly different from 24 significantly less than 24 significantly less than 25

not significantly different from 24

A random sample of 100 people was taken. Eighty of the people in the sample favored Candidate A. We are interested in determining whether or not the proportion of the population in favor of Candidate A is significantly more than 75%. Refer to Exhibit 9-6. At a .05 level of significance, it can be concluded that the proportion of the population in favor of candidate A is significantly greater than 75% not significantly greater than 75% significantly greater than 80% not significantly greater than 80%

not significantly greater than 80%

Refer to Exhibit 10-2. The null hypothesis should be rejected null hypothesis should not be rejected alternative hypothesis should be accepted None of these alternatives is correct.

null hypothesis should not be rejected

For which of the following values of p is the value of p(1 - p) maximized? p = 0.99 p = 0.90 p = 1.0 p = 0.50

p = 0.50

A p-value is the probability, when the null hypothesis is true, of obtaining a sample result that is at least as unlikely as what is observed value of the test statistic probability of a Type II error probability corresponding to the critical value(s) in a hypothesis test

probability, when the null hypothesis is true, of obtaining a sample result that is at least as unlikely as what is observed

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took these 100 customers to check out was 3.0 minutes. It is known that the standard deviation of the checkout time is one minute. Refer to Exhibit 8-2. If the confidence coefficient is reduced to 0.80, the standard error of the mean will increase will decrease remains unchanged becomes negative

remains unchanged

The degrees of freedom associated with a t distribution are a function of the area in the upper tail sample standard deviation confidence coefficient sample size

sample size

In order to determine whether or not there is a significant difference between the hourly wages of two companies, the following data have been accumulated. Company A Company B Sample size 80 60 Sample mean $16.75 $16.25 Population standard deviation $1.00 $0.95 Refer to Exhibit 10-8. The null hypothesis should be rejected should not be rejected should be revised None of these alternatives is correct.

should be rejected

A two-tailed test is performed at a 5% level of significance. The p-value is determined to be 0.09. The null hypothesis must be rejected should not be rejected may or may not be rejected, depending on the sample size has been designed incorrectly

should not be rejected

The following information was obtained from matched samples. Individual Method 1 Method 2 1 7 5 2 5 9 3 6 8 4 7 7 5 5 6 Refer to Exhibit 10-5. If the null hypothesis is tested at the 5% level, the null hypothesis should be rejected should not be rejected should be revised None of these alternatives is correct.

should not be rejected

The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took the customers in the sample to check out was 3.1 minutes. The population standard deviation is known to be 0.5 minutes. We want to test to determine whether or not the mean waiting time of all customers is significantly more than 3 minutes. Refer to Exhibit 9-2. At a .05 level of significance, it can be concluded that the mean of the population is significantly greater than 3 not significantly greater than 3 significantly less than 3 significantly greater then 3.18

significantly greater than 3

The standard error of x-bar1 - x-bar2 is the variance of x-bar1 - x-bar2 variance of the sampling distribution of x-bar1 - x-bar2 standard deviation of the sampling distribution of x-bar1 - x-bar2 difference between the two means

standard deviation of the sampling distribution of x-bar1 - x-bar2

For the interval estimation of m when s is assumed known, the proper distribution to use is the standard normal distribution t distribution with n degrees of freedom t distribution with n - 1 degrees of freedom t distribution with n - 2 degrees of freedom

standard normal distribution

From a population that is normally distributed with an unknown standard deviation, a sample of 25 elements is selected. For the interval estimation of m, the proper distribution to use is the standard normal distribution z distribution t distribution with 26 degrees of freedom t distribution with 24 degrees of freedom

t distribution with 24 degrees of freedom

Independent simple random samples are taken to test the difference between the means of two populations whose variances are not known. The sample sizes are n1 = 32 and n2 = 40. The correct distribution to use is the binomial distribution t distribution with 72 degrees of freedom t distribution with 71 degrees of freedom t distribution with 70 degrees of freedom

t distribution with 70 degrees of freedom

In hypothesis testing if the null hypothesis has been rejected when the alternative hypothesis has been true, a Type I error has been committed a Type II error has been committed either a Type I or Type II error has been committed the correct decision has been made

the correct decision has been made

The smaller the p-value, the greater the evidence against H0 the greater the chance of committing a Type II error the greater the chance of committing a Type I error the less likely you are to reject H0

the greater the evidence against H0

In hypothesis testing, the alternative hypothesis is the hypothesis tentatively assumed true in the hypothesis-testing procedure the hypothesis concluded to be true if the null hypothesis is rejected the maximum probability of a Type I error All of the answers are correct.

the hypothesis concluded to be true if the null hypothesis is rejected

In determining the sample size necessary to estimate a population proportion, which of the following information is not needed? the maximum margin of error that can be tolerated the confidence level required a preliminary estimate of the true population proportion p the mean of the population

the mean of the population

In developing an interval estimate of the population mean, if the population standard deviation is unknown it is impossible to develop an interval estimate a sample proportion can be used the sample standard deviation and t distribution can be used None of the other answers are correct.

the sample standard deviation and t distribution can be used

The t distribution should be used whenever the sample size is less than 30 the sample standard deviation is used to estimate the population standard deviation the population is not normally distributed None of the other answers are correct.

the sample standard deviation is used to estimate the population standard deviation

SSTR = 6,750 H0: m1 = m2 = m3 = m4 SSE = 8,000 Ha: at least one mean is different nT = 20 Refer to Exhibit 10-16. The null hypothesis should be rejected should not be rejected was designed incorrectly None of these alternatives is correct.

was designed incorrectly

If we change a 95% confidence interval estimate to a 99% confidence interval estimate, we can expect the width of the confidence interval to increase width of the confidence interval to decrease width of the confidence interval to remain the same sample size to increase

width of the confidence interval to increase

For a sample size of 30, changing from using the standard normal distribution to using the t distribution in a hypothesis test, will result in the rejection region being smaller will result in the rejection region being larger would have no effect on the rejection region Not enough information is given to answer this question.

will result in the rejection region being smaller

If the margin of error in an interval estimate of m is 4.6, the interval estimate equals x-bar + or - 2.3 x-bar + or - 4.6 x-bar + or - 4.508 x-bar + or - 6.9

x-bar + or - 4.6