Exam 9: A: large-Sample Tests of Hypotheses

In testing the difference between two population means using two independent samples, we use the pooled variance in estimating the standard error of the sampling distribution of the sample mean difference if the populations are normal with equal variances.

(True/False)

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Question 41

Which of the following would be an appropriate alternative hypothesis to test a proportion?

(Multiple Choice)

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Question 42

The probability of correctly accepting a true null hypothesis equals 1 - and is called the confidence level of the hypothesis test.

(True/False)

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Question 43

In testing the difference between two population means using two independent samples, the sampling distribution of the sample mean difference is normal if the sample sizes are both greater than 30.

(True/False)

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Question 44

For testing the difference between two population proportions, under what circumstances should the pooled proportion estimate be used to compute the value of the test statistic?

(Multiple Choice)

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Question 45

If you wish to determine there is evidence that the average starting salary for finance graduates exceeds $42,000, how would you formulate the null and alternative hypotheses?

(Multiple Choice)

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Question 46

In estimating the difference between two population means, if a 90% confidence interval includes 0, then we can be 90% certain that the difference between the two population means is 0.

(True/False)

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Question 47

A two-tailed hypothesis test of the population mean is used when the alternative hypothesis takes the form

(True/False)

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Question 48

In testing vs. a random sample of size 200 produced a sample proportion Given these results, the null hypothesis should not be rejected at = 0.05.

(True/False)

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Question 49

A hypothesis that specifies a range of values for the unknown parameter is called an interval estimate.

(True/False)

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Question 50

The campaign manager for the Conservatives believes that more than 52% of the registered voters will vote Conservative. If you wish to test this claim, the appropriate null and alternative hypotheses are vs.

(True/False)

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Question 51

If the probability of committing a Type I error for a given test is to be decreased, then for a fixed sample size n, what will happen?

(Multiple Choice)

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Question 52

The upper limit of the 85% confidence interval for the population proportion p, given that n = 60 and = 0.20, is 0.274.

(True/False)

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Question 53

A Type II error for a statistical test is committed if we do not reject the null hypothesis when it is false.

(True/False)

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Question 54

Decision makers have more control over Type I error than Type II error.

(True/False)

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Question 55

The width of a confidence interval estimate for a proportion will be wider for a sample size of 100 than for a sample size of 50.

(True/False)

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Question 56

In a one-tailed test about the population proportion p, the p-value is found to be equal to 0.0352. If the test had been two-tailed, the p-value would have been 0.0704.

(True/False)

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Question 57

For a fixed sample size n, as the probability of a Type II error $\beta$ decreases, the probability of a Type I error $\alpha$ increases.

(True/False)

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Question 58

How is a Type II error is committed?

(Multiple Choice)

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Question 59

If we reject the null hypothesis, what are we concluding?

(Multiple Choice)

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Question 60

Showing 41 - 60 of 154

Exam 9: A: large-Sample Tests of Hypotheses

In testing the difference between two population means using two independent samples, we use the pooled variance in estimating the standard error of the sampling distribution of the sample mean difference if the populations are normal with equal variances.

Which of the following would be an appropriate alternative hypothesis to test a proportion?

The probability of correctly accepting a true null hypothesis equals 1 - and is called the confidence level of the hypothesis test.

In testing the difference between two population means using two independent samples, the sampling distribution of the sample mean difference is normal if the sample sizes are both greater than 30.

For testing the difference between two population proportions, under what circumstances should the pooled proportion estimate be used to compute the value of the test statistic?

If you wish to determine there is evidence that the average starting salary for finance graduates exceeds $42,000, how would you formulate the null and alternative hypotheses?

In estimating the difference between two population means, if a 90% confidence interval includes 0, then we can be 90% certain that the difference between the two population means is 0.

A two-tailed hypothesis test of the population mean is used when the alternative hypothesis takes the form

In testing vs. a random sample of size 200 produced a sample proportion Given these results, the null hypothesis should not be rejected at = 0.05.

A hypothesis that specifies a range of values for the unknown parameter is called an interval estimate.

The campaign manager for the Conservatives believes that more than 52% of the registered voters will vote Conservative. If you wish to test this claim, the appropriate null and alternative hypotheses are vs.

If the probability of committing a Type I error for a given test is to be decreased, then for a fixed sample size n, what will happen?

The upper limit of the 85% confidence interval for the population proportion p, given that n = 60 and = 0.20, is 0.274.

A Type II error for a statistical test is committed if we do not reject the null hypothesis when it is false.

Decision makers have more control over Type I error than Type II error.

The width of a confidence interval estimate for a proportion will be wider for a sample size of 100 than for a sample size of 50.

In a one-tailed test about the population proportion p, the p-value is found to be equal to 0.0352. If the test had been two-tailed, the p-value would have been 0.0704.

For a fixed sample size n, as the probability of a Type II error β\betaβ decreases, the probability of a Type I error α\alphaα increases.

How is a Type II error is committed?

If we reject the null hypothesis, what are we concluding?

Describing Data With Graphs

Describing Data With Numerical Measures

Describing Bivariate Data

A: probability and Probability Distributions

B: probability and Probability Distributions

Several Useful Discrete Distributions

The Normal Probability Distribution

Sampling Distributions

Large-Sample Estimation

B: large-Sample Tests of Hypotheses

A: Inference From Small Samples

B: Inference From Small Samples

A: The Analysis of Variance

B: The Analysis of Variance

A: linear Regression and Correlation

B: linear Regression and Correlation

Multiple Regression Analysis

Analysis of Categorical Data

A:nonparametric Statistics

B:nonparametric Statistics

Filters

For a fixed sample size n, as the probability of a Type II error $\beta$ decreases, the probability of a Type I error $\alpha$ increases.