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Q:
Box and whisker plots are often useful for determining whether two populations have distributions that might each be normally distributed.
Q:
In estimating the difference between two population means based on small, independent samples from the two populations, two important assumptions are that the populations each be normally distributed and the populations have equal variances.
Q:
The NCAA is interested in estimating the difference in mean number of daily training hours for men and women athletes on college campuses. It wants 95 percent confidence and will select a sample of 10 men and 10 women for the study. The variances are assumed equal and the populations normally distributed. The sample results are: Men
Women n1 = 10 students
n2 = 10 students 1 = 2.7 hours
2 = 2.4 hours s1 = .30 hours
s2 = .40 hours Based on these data, the lower limit for the difference between population means is 0.15 hours.
Q:
The NCAA is interested in estimating the difference in mean number of daily training hours for men and women athletes on college campuses. It wants 95 percent confidence and will select a sample of 10 men and 10 women for the study. The variances are assumed equal and the populations normally distributed. The sample results are: Men
Women n1 = 10 students
n2 = 10 students 1 = 2.7 hours
2 = 2.4 hours s1 = .30 hours
s2 = .40 hours Based on these sample data, the estimate for the standard deviation of the sampling distribution is found by taking the square root of the sum of the two sample variances.
Q:
The NCAA is interested in estimating the difference in mean number of daily training hours for men and women athletes on college campuses. It wants 95 percent confidence and will select a sample of 10 men and 10 women for the study. The variances are assumed equal and the populations normally distributed. The sample results are: Men
Women n1 = 10 students
n2 = 10 students 1 = 2.7 hours
2 = 2.4 hours s1 = .30 hours
s2 = .40 hours Based on these sample data, the critical value for developing the confidence interval is z = 1.96.
Q:
The NCAA is interested in estimating the difference in mean number of daily training hours for men and women athletes on college campuses. They want 95 percent confidence and will select a sample of 10 men and 10 women for the study. The sample results are: Men
Women n1 = 10 students
n2 = 10 students 1 = 2.7 hours
2 = 2.4 hours s1 = .30 hours
s2 = .40 hours Based on these data, the point estimate is .30 hours.
Q:
The NCAA is interested in estimating the difference in mean number of daily training hours for men and women athletes on college campuses. They want 95 percent confidence and will select a sample of 10 men and 10 women for the study. If the NCAA assumes that the population standard deviations are known, the critical value for the confidence interval is t = 2.1009.
Q:
In estimating the difference between two population means, if a 95 percent confidence interval includes zero, then we can conclude that there is a 95 percent chance that the difference between the two population means is zero.
Q:
The Cranston Hardware Company is interested in estimating the difference in the mean purchase for men customers versus women customers. It wishes to estimate this difference using a 95 percent confidence level. Assume that the variances are equal and the populations normally distributed. The following data represent independent samples from each population: Men
Women 16.49
17.21 33.34
17.46 20.18
15.65 26.39
10.67 28.03
14.07 26.02
19.61 16.08
15.90 32.27
11.17 21.66
24.66 32.32
13.35 29.79
20.87 33.37
22.57 Based on these data, the company can conclude that there is a statistical difference between men and women with regard to mean spending at the hardware store with men tending to spend more on average than women.
Q:
The Cranston Hardware Company is interested in estimating the difference in the mean purchase for men customers versus women customers. It wishes to estimate this difference using a 95 percent confidence level. Assume that the variances are equal and the populations normally distributed. The following data represent independent samples from each population: Men
Women 16.49
17.21 33.34
17.46 20.18
15.65 26.39
10.67 28.03
14.07 26.02
19.61 16.08
15.90 32.27
11.17 21.66
24.66 32.32
13.35 29.79
20.87 33.37
22.57 Based on these data, the upper limit of the interval estimate is approximately $13.82.
Q:
To find a confidence interval for the difference between the means of independent samples, when the variances are unknown but assumed equal, the sample sizes of the two groups must be the same.
Q:
The Cranston Hardware Company is interested in estimating the difference in the mean purchase for men customers versus women customers. It wishes to estimate this difference using a 95 percent confidence level. If the sample size is n = 10 from each population, the samples are independent, and sample standard deviations are used, and the variances are assumed equal, then the critical value will be t = 2.1009.
Q:
For the following z-test statistic, compute the p-value assuming that the hypothesis test is a one-tailed test: z = 2.09.
A) 0.0172
B) 0.0183
C) 0.0415
D) 0.0611
Q:
For the following z-test statistic, compute the p-value assuming that the hypothesis test is a one-tailed test: z = 1.34.
A) 0.0606
B) 0.0815
C) 0.0124
D) 0.0901
Q:
A consumer group plans to test whether a new passenger car that is advertised to have a mean highway miles per gallon of at least 33 actually meets this level. They plan to test the hypothesis using a significance level of 0.05 and a sample size of n = 100 cars. It is believed that the population standard deviation is 3 mpg. Based upon this information, if the "true" population mean is 32.0 mpg, what is the probability that the test will lead the consumer group to reject the claimed mileage for this car?
A) About 0.075
B) Approximately 0.95
C) 0.05
D) None of the above
Q:
If the hypothesis test you are conducting is a two-tailed test, which of the following is a possible step that you could take to increase the power of the test?
A) Reduce the sample size
B) Increase alpha
C) Increase beta
D) Use the t-distribution
Q:
A recent report in which a major pharmaceutical company released the results of testing that had been done on the cholesterol reduction that people could expect if they use the company's new drug indicated that the Type II error probability for a given "true" mean was 0.1250 based on the sample size of n = 64 subjects. Given this, what was the power of the test under these same conditions? The alpha level used in the test was 0.05.
A) 0.95
B) 0.875
C) Essentially zero
D) Power would be undefined in this case since the hypothesis would be rejected.
Q:
A company that sells an online course aimed at helping high-school students improve their SAT scores has claimed that SAT scores will improve by more than 90 points on average if students successfully complete the course. To test this, a national school counseling organization plans to select a random sample of n = 100 students who have previously taken the SAT test. These students will take the company's course and then retake the SAT test. Assuming that the population standard deviation for improvement in test scores is thought to be 30 points and the level of significance for the hypothesis test is 0.05, find the critical value in terms of improvement in SAT points, which would be needed prior to finding a beta.
A) Reject the null if SAT improvement is > 95 points.
B) Reject the null if SAT improvement is < 85.065 points.
C) Reject the null if SAT improvement is > 95.88 points.
D) Reject the null if SAT improvement is > 94.935 points.
Q:
A company that sells an online course aimed at helping high-school students improve their SAT scores has claimed that SAT scores will improve by more than 90 points on average if students successfully complete the course. To test this, a national school counseling organization plans to select a random sample of n = 100 students who have previously taken the SAT test. These students will take the company's course and then retake the SAT test. Assuming that the population standard deviation for improvement in test scores is thought to be 30 points and the level of significance for the hypothesis test is 0.05, what is the probability that the counseling organization will incorrectly "accept" the null hypothesis when, in fact, the true mean increase is actually 95 points?
A) Approximately 0.508
B) About 0.492
C) Approximately 0.008
D) Can't be determined without knowing the sample results.
Q:
A contract calls for the mean diameter of a cylinder to be 1.50 inches. As a quality check, each day a random sample of n = 36 cylinders is selected and the diameters are measured. Assuming that the population standard deviation is thought to be 0.10 inch and that the test will be conducted using an alpha equal to 0.025, what would the probability of a Type II error be?
A) Approximately 0.1267
B) About 0.6789
C) 0.975
D) Can't be determined without knowing the "true" population mean.
Q:
Suppose we want to test H0 : 30 versus H1 : < 30. Which of the following possible sample results based on a sample of size 36 gives the strongest evidence to reject H0 in favor of H1?A) = 28, s = 6B) = 27, s = 4C) = 32, s = 2D) = 26, s = 9
Q:
A consumer group plans to test whether a new passenger car that is advertised to have a mean highway miles per gallon of at least 33 actually meets this level. They plan to test the hypothesis using a significance level of 0.05 and a sample size of n = 100 cars. It is believed that the population standard deviation is 3 mpg. Based upon this information, what is the critical value in terms of miles per gallon that would be needed prior to finding beta?
A) 32.5065
B) 33.4935
C) 33.588
D) 32.412
Q:
A consumer group plans to test whether a new passenger car that is advertised to have a mean highway miles per gallon of at least 33 actually meets this level. They plan to test the hypothesis using a significance level of 0.05 and a sample size of n = 100 cars. It is believed that the population standard deviation is 3 mpg. Based upon this information, if the "true" population mean is 32.0 mpg, what is the probability that the test will lead the consumer group to "accept" the claimed mileage for this car?
A) About 0.45
B) Approximately 0.0455
C) About 0.9545
D) None of the above
Q:
Which of the following will be helpful if the decision maker wishes to reduce the chance of making a Type II error?
A) Increase the level of significance at which the hypothesis test is conducted.
B) Increase the sample size.
C) Both A and B will work.
D) Neither A nor B will be effective.
Q:
The power of a test is measured by its capability of:
A) rejecting a null hypothesis that is true.
B) not rejecting a null hypothesis that is true.
C) rejecting a null hypothesis that is false.
D) not rejecting a null hypothesis that is false.
Q:
For a given sample size n, if the level of significance () is decreased, the power of the test:A) will increase.B) will decrease.C) will remain the same.D) cannot be determined.
Q:
If the Type I error () for a given test is to be decreased, then for a fixed sample size n:A) the Type II error () will also decrease.B) the Type II error () will increase.C) the power of the test will increase.D) a one-tailed test must be utilized.
Q:
Which of the following is not a required step in finding beta?
A) Assuming a true value of the population parameter where the null is false
B) Finding the critical value based on the null hypothesis
C) Converting the critical value from the standard normal distribution to the units of the data
D) Finding the power of the test
Q:
Mike runs for the president of the student government and is interested to know whether the proportion of the student body in favor of him is significantly more than 50 percent. A random sample of 100 students was taken. Fifty-five of them favored Mike. At a 0.05 level of significance, it can be concluded that the proportion of the students in favor of Mike
A) is significantly greater than 50 percent because 55 percent of the sample favored him.
B) is not significantly greater than 50 percent.
C) is significantly greater than 55 percent.
D) is not significantly different from 55 percent.
Q:
After completing sales training for a large company, it is expected that the salesperson will generate a sale on at least 15 percent of the calls he or she makes. To make sure that the sales training process is working, a random sample of n = 400 sales calls made by sales representatives who have completed the training have been selected and the null hypothesis is to be tested at 0.05 alpha level. Suppose that a sale is made on 36 of the calls. Based on these sample data, which of the following is true?
A) The null hypothesis should be rejected since the test statistic falls in the lower tail rejection region.
B) The null hypothesis is supported since the sample results do not fall in the rejection region.
C) There is insufficient evidence to reject the null hypothesis and the sample proportion is different from the hypothesized proportion due to sampling error.
D) It is possible that a Type II statistical error has been committed.
Q:
After completing sales training for a large company, it is expected that the salesperson will generate a sale on at least 15 percent of the calls he or she makes. To make sure that the sales training process is working, a random sample of n = 400 sales calls made by sales representatives who have completed the training have been selected and the null hypothesis is to be tested at 0.05 alpha level. Suppose that a sale is made on 36 of the calls. Based on this information, what is the test statistic for this test?
A) Approximately 0.1417
B) About z = -3.35
C) z = -1.645
D) t = -4.567
Q:
Woof Chow Dog Food Company believes that it has a market share of 25 percent. It surveys n = 100 dog owners and ask whether or not Woof Chow is their regular brand of dog food, and 23 people say yes. Based upon this information, what is the value of the test statistic?
A) -0.462
B) -0.475
C) 0.462
D) 0.475
Q:
Woof Chow Dog Food Company believes that it has a market share of 25 percent. It surveys n = 100 dog owners and ask whether or not Woof Chow is their regular brand of dog food, and 23 people say yes. Based upon this information, what is the critical value if the hypothesis is to be tested at the 0.05 level of significance?
A) 1.28
B) 1.645
C) 1.96
D) 2.575
Q:
Woof Chow Dog Food Company believes that it has a market share of 25 percent. It surveys n = 100 dog owners and ask whether or not Woof Chow is their regular brand of dog food. The appropriate null and alternate hypotheses are:A) H0 : = .25Ha : .25B) H0 : p = .25Ha : p .25C) H0 : = .25Ha : .25D) H0 : p .25Ha : p > .25
Q:
The manager of an online shop wants to determine whether the mean length of calling time of its customers is significantly more than 3 minutes. A random sample of 100 customers was taken. The average length of calling time in the sample was 3.1 minutes with a standard deviation of 0.5 minutes. At a 0.05 level of significance, it can be concluded that the mean of the population is:
A) significantly greater than 3.
B) not significantly greater than 3.
C) significantly less than 3.
D) not significantly different from 3.10.
Q:
A house cleaning service claims that it can clean a four bedroom house in less than 2 hours. A sample of n = 16 houses is taken and the sample mean is found to be 1.97 hours and the sample standard deviation is found to be 0.1 hours. Using a 0.05 level of significance the correct conclusion is:
A) reject the null because the test statistic (-1.2) is < the critical value (1.7531).
B) do not reject the null because the test statistic (1.2) is > the critical value (-1.7531).
C) reject the null because the test statistic (-1.7531) is < the critical value (-1.2).
D) do not reject the null because the test statistic (-1.2) is > the critical value (-1.7531).
Q:
A major airline is concerned that the waiting time for customers at its ticket counter may be exceeding its target average of 190 seconds. To test this, the company has selected a random sample of 100 customers and times them from when the customer first arrives at the checkout line until he or she is at the counter being served by the ticket agent. The mean time for this sample was 202 seconds with a standard deviation of 28 seconds. Given this information and the desire to conduct the test using an alpha level of 0.02, which of the following statements is true?
A) The chance of a Type II error is 1 - 0.02 = 0.98.
B) The test to be conducted will be structured as a two-tailed test.
C) The test statistic will be approximately t = 4.286, so the null hypothesis should be rejected.
D) The sample data indicate that the difference between the sample mean and the hypothesized population mean should be attributed only to sampling error.
Q:
When testing a two-tailed hypothesis using a significance level of 0.05, a sample size of n = 16, and with the population standard deviation unknown, which of the following is true?
A) The null hypothesis can be rejected if the sample mean gets too large or too small compared with the hypothesized mean.
B) The alpha probability must be split in half and a rejection region must be formed on both sides of the sampling distribution.
C) The test statistic will be a t-value.
D) All of the above are true.
Q:
A concern of Major League Baseball is that games last too long. Some executives in the league's headquarters believe that the mean length of games this past year exceeded 3 hours (180 minutes). To test this, the league selected a random sample of 80 games and found the following results: = 193 minutes and s = 16 minutes.
Based on these results, if the null hypothesis is tested using an alpha level equal to 0.10, which of the following is true?
A) The null hypothesis should be rejected if > 182.31.
B) The test statistic is t = 1.2924.
C) Based on the sample data, the null hypothesis cannot be rejected.
D) It is possible that when the hypothesis test is completed, a Type II statistical error has been made.
Q:
The R.D. Wilson Company makes a soft drink dispensing machine that allows customers to get soft drinks from the machine in a cup with ice. When the machine is running properly, the average number of fluid ounces in the cup should be 14. Periodically the machines need to be tested to make sure that they have not gone out of adjustment. To do this, six cups are filled by the machine and a technician carefully measures the volume in each cup. In one such test, the following data were observed: 14.25
13.7
14.02 14.13
13.99
14.04 Based on these sample data, which of the following is true if the significance level is .05?
A) No conclusion can be reached about the status of the machine based on a sample size of only six cups.
B) The null hypothesis cannot be rejected since the test statistic is approximately t = 0.20, which is not in the rejection region.
C) The null hypothesis can be rejected since the sample mean is greater than 14.
D) The null can be rejected because the majority of the sample values exceed 14.
Q:
The R.D. Wilson Company makes a soft drink dispensing machine that allows customers to get soft drinks from the machine in a cup with ice. When the machine is running properly, the average number of fluid ounces in the cup should be 14. Periodically the machines need to be tested to make sure that they have not gone out of adjustment. To do this, six cups are filled by the machine and a technician carefully measures the volume in each cup. In one such test, the following data were observed: 14.2513.714.0214.1313.9914.04Which of the following would be the correct null hypothesis if the company wishes to test the machine?A) H0 : = 14 ouncesB) H0: = 14 ouncesC) H0 : 14 ouncesD) H0 : 14 ounces
Q:
The cost of a college education has increased at a much faster rate than costs in general over the past twenty years. In order to compensate for this, many students work part- or full-time in addition to attending classes. At one university, it is believed that the average hours students work per week exceeds 20. To test this at a significance level of 0.05, a random sample of n = 20 students was selected and the following values were observed: 26
15
10
40 10
20
30
36 40
0
5
10 20
32
16
12 40
36
10
0 Based on these sample data, the critical value expressed in hours:
A) is approximately equal to 25.26 hours.
B) is approximately equal to 25.0 hours.
C) cannot be determined without knowing the population standard deviation.
D) is approximately 22 hours.
Q:
The cost of a college education has increased at a much faster rate than costs in general over the past twenty years. In order to compensate for this, many students work part- or full-time in addition to attending classes. At one university, it is believed that the average hours students work per week exceeds 20. To test this at a significance level of 0.05, a random sample of n = 20 students was selected and the following values were observed: 26
15
10
40 10
20
30
36 40
0
5
10 20
32
16
12 40
36
10
0 Based on these sample data, which of the following statements is true?
A) The standard error of the sampling distribution is approximately 3.04.
B) The test statistic is approximately t = 0.13.
C) The research hypothesis that the mean hours worked exceeds 20 is not supported by these sample data.
D) All of the above are true.
Q:
A company that makes shampoo wants to test whether the average amount of shampoo per bottle is 16 ounces. The standard deviation is known to be 0.20 ounces. Assuming that the hypothesis test is to be performed using 0.10 level of significance and a random sample of n = 64 bottles, how large could the sample mean be before they would reject the null hypothesis?
A) 16.2 ounces
B) 16.049 ounces
C) 15.8 ounces
D) 16.041 ounces
Q:
A company that makes shampoo wants to test whether the average amount of shampoo per bottle is 16 ounces. The standard deviation is known to be 0.20 ounces. Assuming that the hypothesis test is to be performed using 0.10 level of significance and a random sample of n = 64 bottles, which of the following would be the correct formulation of the null and alternative hypotheses?A) H0 : = 16HA : = 16B) H0 : = 16HA : 16C) H0 : 16HA : < 16D) H0 : 16HA : < 16
Q:
A company that makes shampoo wants to test whether the average amount of shampoo per bottle is 16 ounces. The standard deviation is known to be 0.20 ounces. Assuming that the hypothesis test is to be performed using 0.10 level of significance and a random sample of n = 64 bottles, which of the following would be the upper tail critical value?
A) 1.28
B) 1.645
C) 1.96
D) 2.575
Q:
The reason for using the t-distribution in a hypothesis test about the population mean is:
A) the population standard deviation is unknown.
B) it results in a lower probability of a Type I error occurring.
C) it provides a smaller critical value than the standard normal distribution for a given sample size.
D) the population is not normally distributed.
Q:
In a two-tailed hypothesis test for a population mean, an increase in the sample size will:
A) have no effect on whether the null hypothesis is true or false.
B) have no effect on the significance level for the test.
C) result in a sampling distribution that has less variability.
D) All of the above are true.
Q:
A hypothesis test is to be conducted using an alpha = .05 level. This means:
A) there is a 5 percent chance that the null hypothesis is true.
B) there is a 5 percent chance that the alternative hypothesis is true.
C) there is a maximum 5 percent chance that a true null hypothesis will be rejected.
D) there is a 5 percent chance that a Type II error has been committed.
Q:
If the p value is less than in a two-tailed test,A) the null hypothesis should not be rejected.B) the null hypothesis should be rejected.C) a one-tailed test should be used.D) More information is needed to reach a conclusion about the null hypothesis.
Q:
If an economist wishes to determine whether there is evidence that average family income in a community exceeds $25,000. The best null hypothesis is:A) = 25,000.B) > 25,000.C) 25,000.D) 25,000.
Q:
If we are performing a two-tailed test of whether = 100, the probability of detecting a shift of the mean to 105 will be ________ the probability of detecting a shift of the mean to 110.A) less thanB) greater thanC) equal toD) not comparable to
Q:
Which of the following would be an appropriate null hypothesis?
A) The mean of a population is equal to 55.
B) The mean of a sample is equal to 55.
C) The mean of a population is greater than 55.
D) The mean of a sample is greater than 55.
Q:
In a hypothesis test involving a population mean, which of the following would be an acceptable formulation?A) H0 : $1,700Ha : > $1,700B) H0 : > $1,700Ha : $1,700C) H0 : $1,700Ha : > $1,700D) None of the above is a correct formulation.
Q:
Which of the following statements is true?
A) The decision maker controls the probability of making a Type I statistical error.
B) Alpha represents the probability of making a Type II error.
C) Alpha and beta are directly related such that when one is increased the other will increase also.
D) The alternative hypothesis should contain the equality.
Q:
When someone is on trial for suspicion of committing a crime, the hypotheses are:
H0 : innocent
HA : guilty
Which of the following is correct?
A) Type I error is acquitting a guilty person.
B) Type I error is convicting an innocent person.
C) Type II error is acquitting an innocent person.
D) Type II error is convicting an innocent person.
Q:
A major airline has stated in an industry report that its mean onground time between domestic flights is less than 18 minutes. To test this, the company plans to sample 36 randomly selected flights and use a significance level of .10. Assuming that the population standard deviation is known to be 4.0 minutes, if the true population mean is 16 minutes, the decision maker could end up making either a Type I or a Type II error depending on the sample result.
Q:
A major airline has stated in an industry report that its mean onground time between domestic flights is less than 18 minutes. To test this, the company plans to sample 36 randomly selected flights and use a significance level of 0.10. Assuming that the population standard deviation is known to be 4.0 minutes, the probability that the null hypothesis will be "accepted" if the true population mean is 16 minutes is approximately 0.955.
Q:
The director of the city Park and Recreation Department claims that the mean distance people travel to the city's greenbelt is more than 5.0 miles. Assuming that the population standard deviation is known to be 1.2 miles and the significance level to be used to test the hypothesis is 0.05 when a sample size of n = 64 people are surveyed, the probability of a Type II error is approximately .4545 when the "true" population mean is 5.5 miles.
Q:
A city newspaper has stated that the average time required to sell a used car advertised in the paper is less than 5 days. Assuming that the population standard deviation is 2.1 days, if the "true" population mean is 4.1 days and a sample size of n = 49 is used with an alpha equal to 0.05, the probability that the hypothesis test will lead to a Type II error is approximately .0869.
Q:
The probability of a Type II error decreases as the "true" population value gets farther from the hypothesized population value, given that everything else is held constant.
Q:
To calculate beta requires making a "what if" assumption about the true population parameter, where the "what-if" value is one that would cause the null hypothesis to be false.
Q:
If a decision maker wishes to reduce the chance of making a Type II error, one option is to increase the sample size.
Q:
Type II errors are typically greater for two-tailed hypothesis tests than for one-tailed tests.
Q:
If a decision maker is concerned that the chance of making a Type II error is too large, one option that will help reduce the risk is to reduce the significance level.
Q:
Choosing an alpha of 0.01 will cause beta to equal 0.99.
Q:
The chance of making a Type II statistical error increases if the "true" population mean is closer to the hypothesized population mean, all other factors held constant.
Q:
An article in an operations management journal recently stated that a formal hypothesis test rejected the hypothesis that mean employee productivity was less than $45.70 per hour in the wood processing industry. Given this conclusion, it is possible that a Type I statistical error was committed.
Q:
In a hypothesis test, increasing the sample size will generally result in a smaller chance of making a Type I error since sampling error is likely to be reduced.
Q:
One claim states the IRS conducts audits for not more than 5 percent of total tax returns each year. In order to test this claim statistically, the appropriate null and alternative hypotheses are:H0 : 0.05Ha : > 0.05
Q:
A cell phone company believes that 90 percent of their customers are satisfied. They survey a sample of n = 100 customers and find that 82 say they are satisfied. In calculating the standard error of the sampling distribution (σp) the proportion to use is 0.82.
Q:
A major package delivery company claims that at least 95 percent of the packages it delivers reach the destination on time. As part of the evidence in a lawsuit against the package company, a random sample of n = 200 packages was selected. A total of 188 of these packages were delivered on time. Using a significance level of .05, the test statistic for this test is approximately z = -0.65.
Q:
A major package delivery company claims that at least 95 percent of the packages it delivers reach the destination on time. As part of the evidence in a lawsuit against the package company, a random sample of n = 200 packages was selected. A total of 188 of these packages were delivered on time. Using a significance level of 0.05, the critical value for this hypothesis test is approximately 0.90.
Q:
When the hypothesized proportion is close to 0.50, the spread in the sampling distribution of is greater than when the hypothesized proportion is close to 0.0 or 1.0.
Q:
When testing a hypothesis involving population proportions, an increase in sample size will result in a smaller chance of making a Type I statistical error.
Q:
Aceco has a contract with a supplier to ship parts that contain no more than three percent defects. When a large shipment of parts comes in, Aceco samples n = 150. Based on the results of the sample, they either accept the shipment or reject it. If Aceco wants no more than a 0.10 chance of rejecting a good shipment, the cut-off between accepting and rejecting should be 0.0478 or 4.78 percent of the sample.
Q:
A cell phone company believes that 90 percent of its customers are satisfied with their service. They survey n = 30 customers. Based on this, it is acceptable to assume the sample distribution is normally distributed.
Q:
A company that makes and markets a device that is aimed at helping people quit smoking claims that at least 70 percent of the people who have used the product have quit smoking. To test this, a random sample of n = 100 product users was selected. The critical value for the hypothesis test using a significance level of 0.05 would be approximately -1.645.
Q:
A company that makes and markets a device that is aimed at helping people quit smoking claims that at least 70 percent of the people who have used the product have quit smoking. To test this, a random sample of n = 100 product users was selected. Of these, 65 people were found to have quit smoking. Given these results, the test statistic value is z = -1.0911.
Q:
The executive director of the United Way believes that more than 24 percent of the employees in the high-tech industry have made voluntary contributions to the United Way. In order to test this statistically, the appropriate null and alternative hypotheses are:H0 : .24HA : > .24