Question 1

The Central Limit Theorem (CLT) implies that:

Accepted Answer

A) the population will be approximately normal if n ≥ 30. 
B) repeated samples must be taken to obtain normality. 
C) the distribution of the mean is approximately normal for large n. 
D) the mean follows the same distribution as the population. 
A) the population will be approximately normal if n ≥ 30. 
B) repeated samples must be taken to obtain normality. 
C) the distribution of the mean is approximately normal for large n. 
D) the mean follows the same distribution as the population. C

Question 2

Sampling variation is not controllable by the statistician.

Accepted Answer

A) True 
 B)False  True

Question 3

A sampling distribution describes the distribution of:

Accepted Answer

A) a parameter. 
B) a statistic. 
C) either a parameter or a statistic. 
D) neither a parameter nor a statistic. 
A) a parameter. 
B) a statistic. 
C) either a parameter or a statistic. 
D) neither a parameter nor a statistic. B

Question 4

A 99 percent confidence interval has higher confidence but less precision than a 95 percent confidence interval.

Accepted Answer

A) True 
 B)False

Question 5

The sample proportion is always the midpoint of a confidence interval for the population proportion.

Accepted Answer

A) True 
 B)False

Question 6

The standard error of the sample proportion is largest when π = .50.

Accepted Answer

A) True 
 B)False

Question 7

In comparing estimators, the more efficient estimator will have a smaller standard error.

Accepted Answer

A) True 
 B)False

Question 8

In constructing confidence intervals, it is conservative to use the z distribution when n ≥ 30.

Accepted Answer

A) True 
 B)False

Question 9

An airport traffic analyst wants to estimate the proportion of daily takeoffs by small business jets (as opposed to commercial passenger jets or other aircraft) with an error of ± 4 percent with 90 percent confidence. What sample size should the analyst use?

Accepted Answer

A) 385 
B) 601 
C) 410 
D) 423 
A) 385 
B) 601 
C) 410 
D) 423

Question 10

A university wants to estimate the average distance that commuter students travel to get to class with an error of ± 3 miles and 90 percent confidence. What sample size would be needed, assuming that travel distances are normally distributed with a range of X = 0 to X = 50 miles, using the Empirical Rule μ ± 3σ to estimate σ.

Accepted Answer

A) About 28 students 
B) About 47 students 
C) About 30 students 
D) About 21 students 
A) About 28 students 
B) About 47 students 
C) About 30 students 
D) About 21 students

Question 11

The standard deviation of the sample proportion p = x/n increases as n increases.

Accepted Answer

A) True 
 B)False

Question 12

If σ = 25, find the sample size to estimate the mean with an error of ± 3 and 90 percent confidence (rounded to the next higher integer).

Accepted Answer

A) 426 
B) 512 
C) 267 
D) 188 
A) 426 
B) 512 
C) 267 
D) 188

Question 13

Sampling error can be avoided:

Accepted Answer

A) by using an unbiased estimator. 
B) by eliminating nonresponses (e.g., older people). 
C) by no method under the statistician's control. 
D) either by using an unbiased estimator or by eliminating nonresponse. 
A) by using an unbiased estimator. 
B) by eliminating nonresponses (e.g., older people). 
C) by no method under the statistician's control. 
D) either by using an unbiased estimator or by eliminating nonresponse.

Question 14

The width of a confidence interval for μ is not affected by:

Accepted Answer

A) the sample size. 
B) the confidence level. 
C) the standard deviation. 
D) the sample mean. 
A) the sample size. 
B) the confidence level. 
C) the standard deviation. 
D) the sample mean.

Question 15

In which situation may the sample proportion safely be assumed to follow a normal distribution?

Accepted Answer

A) 12 successes in a sample of 72 items 
B) 8 successes in a sample of 40 items 
C) 6 successes in a sample of 200 items 
D) 4 successes in a sample of 500 items 
A) 12 successes in a sample of 72 items 
B) 8 successes in a sample of 40 items 
C) 6 successes in a sample of 200 items 
D) 4 successes in a sample of 500 items

Question 16

In constructing a confidence interval for a mean, the width of the interval is dependent on the sample size, the confidence level, and the population standard deviation.

Accepted Answer

A) True 
 B)False

Question 17

Ceteris paribus, the narrowest confidence interval for π is achieved when p = .50.

Accepted Answer

A) True 
 B)False

Question 18

In a confidence interval, the finite population correction factor (FPCF) can be ignored when:

Accepted Answer

A) n = 100 and N = 700. 
B) n = 50 and N = 200. 
C) n = 6 and N = 500. 
D) n = 8 and N = 80. 
A) n = 100 and N = 700. 
B) n = 50 and N = 200. 
C) n = 6 and N = 500. 
D) n = 8 and N = 80.

Question 19

In a survey, 858 out of 2600 homeowners said they expected good economic conditions to continue for the next 12 months. Construct a 95 percent confidence interval for "good times" in the next 12 months.

Accepted Answer

The confid

Question 20

In a random sample of 810 women employees, it is found that 81 would prefer working for a female boss. The width of the 95 percent confidence interval for the proportion of women who prefer a female boss is:

Accepted Answer

A) ± .0288 
B) ± .0105 
C) ± .0207 
D) ± .0196 
A) ± .0288 
B) ± .0105 
C) ± .0207 
D) ± .0196

The Central Limit Theorem (CLT) implies that:

Sampling variation is not controllable by the statistician.

A sampling distribution describes the distribution of:

A 99 percent confidence interval has higher confidence but less precision than a 95 percent confidence interval.

The sample proportion is always the midpoint of a confidence interval for the population proportion.

The standard error of the sample proportion is largest when π = .50.

In comparing estimators, the more efficient estimator will have a smaller standard error.

In constructing confidence intervals, it is conservative to use the z distribution when n ≥ 30.

An airport traffic analyst wants to estimate the proportion of daily takeoffs by small business jets (as opposed to commercial passenger jets or other aircraft) with an error of ± 4 percent with 90 percent confidence. What sample size should the analyst use?

The standard deviation of the sample proportion p = x/n increases as n increases.

If σ = 25, find the sample size to estimate the mean with an error of ± 3 and 90 percent confidence (rounded to the next higher integer).

Sampling error can be avoided:

The width of a confidence interval for μ is not affected by:

In which situation may the sample proportion safely be assumed to follow a normal distribution?

In constructing a confidence interval for a mean, the width of the interval is dependent on the sample size, the confidence level, and the population standard deviation.

Ceteris paribus, the narrowest confidence interval for π is achieved when p = .50.

In a confidence interval, the finite population correction factor (FPCF) can be ignored when:

In a survey, 858 out of 2600 homeowners said they expected good economic conditions to continue for the next 12 months. Construct a 95 percent confidence interval for "good times" in the next 12 months.

In a random sample of 810 women employees, it is found that 81 would prefer working for a female boss. The width of the 95 percent confidence interval for the proportion of women who prefer a female boss is:

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Multiple Regression

Time Series Analysis

Chi-Square Tests

Nonparametric Tests

Quality Management

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Exam 8: Sampling Distributions and Estimation

The Central Limit Theorem (CLT) implies that:

Sampling variation is not controllable by the statistician.

A sampling distribution describes the distribution of:

A 99 percent confidence interval has higher confidence but less precision than a 95 percent confidence interval.

The sample proportion is always the midpoint of a confidence interval for the population proportion.

The standard error of the sample proportion is largest when π = .50.

In comparing estimators, the more efficient estimator will have a smaller standard error.

In constructing confidence intervals, it is conservative to use the z distribution when n ≥ 30.

An airport traffic analyst wants to estimate the proportion of daily takeoffs by small business jets (as opposed to commercial passenger jets or other aircraft) with an error of ± 4 percent with 90 percent confidence. What sample size should the analyst use?

The standard deviation of the sample proportion p = x/n increases as n increases.

If σ = 25, find the sample size to estimate the mean with an error of ± 3 and 90 percent confidence (rounded to the next higher integer).

Sampling error can be avoided:

The width of a confidence interval for μ is not affected by:

In which situation may the sample proportion safely be assumed to follow a normal distribution?

In constructing a confidence interval for a mean, the width of the interval is dependent on the sample size, the confidence level, and the population standard deviation.

Ceteris paribus, the narrowest confidence interval for π is achieved when p = .50.

In a confidence interval, the finite population correction factor (FPCF) can be ignored when:

In a survey, 858 out of 2600 homeowners said they expected good economic conditions to continue for the next 12 months. Construct a 95 percent confidence interval for "good times" in the next 12 months.

In a random sample of 810 women employees, it is found that 81 would prefer working for a female boss. The width of the 95 percent confidence interval for the proportion of women who prefer a female boss is:

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Multiple Regression

Time Series Analysis

Chi-Square Tests

Nonparametric Tests

Quality Management

Filters