m4 test

13. We use the t distribution to make a confidence interval for the population mean if the population from which the sample is drawn is (approximately) normally distributed, the population standard deviation is unknown, and the sample size is at least: A) 30 B) 100 C) 50 D) 2

D) 2

In a hypothesis test, a Type I error occurs when: A) a false null hypothesis is rejected C) a false null hypothesis is not rejected B) a true null hypothesis is not rejected D) a true null hypothesis is rejected

D) a true null hypothesis is rejected

A one-tailed hypothesis test contains: A) one rejection region and two nonrejection regions B) two rejection regions and one nonrejection region C) two rejection regions and two nonrejection regions D) one rejection region and one nonrejection region

D) one rejection region and one nonrejection region

b. Suppose the confidence interval obtained in part a is too wide. Select all of the ways the width of this interval can be reduced. Increasing the sample size Increasing the confidence level Lowering the confidence level Lowering the sample size

Increasing the sample size Lowering the confidence level

Which of the following conditions is required to use the t distribution to make a confidence interval for the population mean? A) The population from which the sample is drawn is (approximately) normally distributed. B) The sample size is at least 30. C) The population from which the sample is drawn has a t distribution. D) The population standard deviation is known.

A) The population from which the sample is drawn is (approximately) normally distributed.

In a one-tailed hypothesis test, a critical point is a point that divides the area under the sampling distribution of a: A) statistic into one rejection region and one nonrejection region B) parameter into one rejection region and one nonrejection region C) statistic into one rejection region and two nonrejection regions D) parameter into two rejection regions and one nonrejection region

A) statistic into one rejection region and one nonrejection region

In a two-tailed hypothesis test, the two critical points are the points that divide the area under the sampling distribution of a: A) statistic into two rejection regions and one nonrejection region B) parameter into one rejection region and one nonrejection region C) statistic into one rejection region and two nonrejection regions D) parameter into two rejection regions and one nonrejection region

A) statistic into two rejection regions and one nonrejection region

Briefly explain the meaning of an estimator and an estimate. An estimator is a prediction of the mean based on the population, while an estimate is a prediction of the mean based on a sample. An estimator is a sample statistic used to estimate a population parameter, while an estimate is the value(s) assigned to a population parameter based on the value of a sample statistic. An estimator is an interval where one is confident to a certain percent that the value of interest is in the interval, while an estimate is the value of a sample statistic used to estimate a population parameter. An estimator is the value(s) assigned to a population parameter based on the value of a sample statistic, while an estimate is a sample statistic used to estimate a population parameter. An estimator is the value of a sample statistic used to estimate a population parameter, while an estimate is an interval where one is confident to a certain percent that the value of interest is in the interval.

An estimator is a sample statistic used to estimate a population parameter, while an estimate is the value(s) assigned to a population parameter based on the value of a sample statistic.

5. The width of a confidence interval depends on the size of the: A) population mean B) margin of error C) sample mean D) none of these

B) margin of error

The alternative hypothesis is a claim about a: A) parameter, where the claim is assumed to be true until it is declared false B) parameter, where the claim is assumed to be true if the null hypothesis is declared false C) statistic, where the claim is assumed to be true if the null hypothesis is declared false D) statistic, where the claim is assumed to be false until it is declared true

B) parameter, where the claim is assumed to be true if the null hypothesis is declared false

The null hypothesis is a claim about a: A) parameter, where the claim is assumed to be false until it is declared true B) parameter, where the claim is assumed to be true until it is declared false C) statistic, where the claim is assumed to be false until it is declared true D) statistic, where the claim is assumed to be true until it is declared false

B) parameter, where the claim is assumed to be true until it is declared false

A two-tailed hypothesis test contains: A) one rejection region and two nonrejection regions B) two rejection regions and one nonrejection region C) two rejection regions and two nonrejection regions D) one rejection region and one nonrejection region

B) two rejection regions and one nonrejection region

In a hypothesis test, a Type II error occurs when: A) a false null hypothesis is rejected C) a false null hypothesis is not rejected B) a true null hypothesis is not rejected D) a true null hypothesis is rejected

C) a false null hypothesis is not rejected

For most distributions, we can use the normal distribution to make a confidence interval for a population mean provided that the population standard deviation is known and the sample size is: A) greater than 30 C) greater than or equal to 30 B) less than 25 D) greater than 100

C) greater than or equal to 30

7. To decrease the width of a confidence interval, we should always prefer to: A) lower the confidence level C) increase the sample size B) increase the confidence level D) decrease the sample size

C) increase the sample size

6. You can decrease the width of a confidence interval by: A) lowering the confidence level or decreasing the sample size B) increasing the confidence level or decreasing the sample size C) lowering the confidence level or increasing the sample size D) increasing the confidence level or increasing the sample size

C) lowering the confidence level or increasing the sample size

In a hypothesis test, the probability of committing a Type I error is called the: A) confidence level B) confidence interval C) significance level D) beta error

C) significance level

We use the t distribution to perform a hypothesis test about the population mean when: A) the population from which the sample is drawn is approximately normal and the population standard deviation is known B) the population from which the sample is drawn is not approximately normal and the population standard deviation is known C) the population from which the sample is drawn is approximately normal and the population standard deviation is unknown D) the population from which the sample is drawn is not approximately normal and the population standard deviation is unknown

C) the population from which the sample is drawn is approximately normal and the population standard deviation is unknown

2. The margin of error for the estimation of the population mean, assuming is known, is: A) z multiplied by the o B) z multiplied by t C) z multiplied by the ox D) z multiplied by the x

C) z multiplied by the ox

Explain the meaning of a point estimate and an interval estimate. The value of a sample statistic used to estimate a population parameter is called a point estimate. In interval estimation, an interval is constructed around the point estimate, and it is stated that this interval is likely to contain the corresponding population parameter. The value of a sample statistic used to estimate a population parameter is called an interval estimate. A point estimate is an interval that is constructed around the interval estimate, and it is stated that this interval is likely to contain the corresponding population parameter. A point estimate is a population parameter used in calculations while an interval estimate is an interval that is constructed around the point estimate, and it is stated that this interval is likely to contain the corresponding population parameter. The value of a sample statistic used to estimate the standard deviation is an interval estimate, and a point estimate is the value of a sample statistic used to estimate the mean. The value of a sample statistic used to estimate the mean is an interval estimate, and a point estimate is the value of a sample statistic used to estimate the standard deviation.

The value of a sample statistic used to estimate a population parameter is called a point estimate. In interval estimation, an interval is constructed around the point estimate, and it is stated that this interval is likely to contain the corresponding population parameter.