Question 1

Stratified random sampling involves selecting a simple random sample from each of a given number of subpopulations, called strata.

Accepted Answer

A) True 
 B)False

Question 2

If a sample is selected at random, the main reason that the sample mean   might be different than the corresponding population mean   is that the sample might be biased.

Accepted Answer

A) True 
 B)False

Question 3

The sampling distribution of the sample proportion   can be approximated by a normal distribution as long as the population proportion p is very close to .50.

Accepted Answer

A) True 
 B)False

Question 4

As a general rule, the normal distribution provides a good approximation to the sampling distribution of the sample proportion   only if:

Accepted Answer

A)  the sample size n is greater than 30 
B)  the sample size n is greater than 100 
C)  the population proportion p is greater than 0.50 
D)  the underlying population has a small standard deviation and n is large 
E)  np and n(1-p) are both greater than 5 
A)  the sample size n is greater than 30 
B)  the sample size n is greater than 100 
C)  the population proportion p is greater than 0.50 
D)  the underlying population has a small standard deviation and n is large 
E)  np and n(1-p) are both greater than 5

Question 5

Small haphazard changes in a process variable due to alteration in the production environment that is not controllable are said to be assignable causes.

Accepted Answer

A) True 
 B)False

Question 6

A candy bar company is interested in reducing the percent defective candy bars made, where a defective candy bar has too few almonds by weight. The company randomly samples 100 candy bars a day for 5 days and finds the percent defective to be 0.0200, 0.0125, 0.0225, 0.0100, and 0.0150. The company wants to construct a control chart for the proportion defective in samples of size n = 100.
Estimate the process fraction defective p.
______________
Estimate the standard deviation of the sample proportions.
______________
What are the control limits?
UCL = ______________
LCL = ______________
How are these control limits used?
________________________________________________________

Accepted Answer

0.016; 0.0125; 0.0535; 0.00; W

Question 7

When all possible simple random samples of size n are drawn from a population that is normally distributed, the sampling distribution of the sample means   will be normal regardless of sample size n.

Accepted Answer

A) True 
 B)False

Question 8

Twenty five samples of size 1000 each were drawn from a manufacturing process and the number of defectives in each sample was counted. The average sample proportion was 0.05. The upper control limit for the p chart is:

Accepted Answer

A)  0.0475 
B)  0.0206 
C)  0.0293 
D)  0.0707 
E)  0.0635 
A)  0.0475 
B)  0.0206 
C)  0.0293 
D)  0.0707 
E)  0.0635

Question 9

The simple random sample is a subset of a frame, or of an associated population, chosen in such a fashion that every possible subset of like size has an equal chance of being selected.

Accepted Answer

A) True 
 B)False

Question 10

If random samples of size n = 36 are drawn from a nonnormal population with finite mean   and standard deviation   , then the sampling distribution of the sample mean   is approximately normally distributed with mean   and standard deviation

Accepted Answer

A) True 
 B)False

Question 11

The distribution of the amount spent for childcare in a Midwestern city has a mean of $675 and a standard deviation of $80. A random sample of 64 families paying for childcare is selected.
Is the sampling distribution of the sample mean approximately normal?
______________
What is the mean?
______________
What is the standard deviation?
______________
Find the probability that the sample mean is between $645 and $700.
______________
Find the probability that the sample mean is less than $700.
______________

Accepted Answer

Yes; 675;

Question 12

The Central Limit Theorem is used to describe the sampling distributions of statistics, such as   and   , when the population is known to be normally distributed.

Accepted Answer

A) True 
 B)False

Question 13

As the sample size increases, the standard error of the sample mean decreases.

Accepted Answer

A) True 
 B)False

Question 14

If the variation in a process variable is solely random, the process is said to be in control.

Accepted Answer

A) True 
 B)False

Question 15

A sampling distribution is defined as a sample chosen in such a way that every possible subset of like size has an equal chance of being selected.

Accepted Answer

A) True 
 B)False

Question 16

If the monthly rent of all one-bedroom apartments in a small town are known to be normally distributed with a mean equal to $175 a month and standard deviation of $35, which of the following would be the highest individual rent that you might expect to find?

Accepted Answer

A)  about $195 
B)  about $210 
C)  about $245 
D)  about $280 
E)  More information is needed to answer the question. 
A)  about $195 
B)  about $210 
C)  about $245 
D)  about $280 
E)  More information is needed to answer the question.

Question 17

The latest U.S. census shows the population aged 25 to 40 to be 48% male and 52% female. A market research firm interested in the buying habits of young adults aged 25 to 40 instructs its interviewers to sample 300 persons, 144 of whom are to be men and 156 of whom are to be women. This is an example of a quota sample.

Accepted Answer

A) True 
 B)False

Question 18

Sixty samples of size 600 each were drawn from a manufacturing process and the number of defectives in each sample was counted. The average sample proportion was 0.04. The lower control limit for the p chart is:

Accepted Answer

A)  0.008 
B)  0.016 
C)  0.064 
D)  0.048 
E)  0.032 
A)  0.008 
B)  0.016 
C)  0.064 
D)  0.048 
E)  0.032

Question 19

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if the sample size n is greater than or equal to 30.

Accepted Answer

A) True 
 B)False

Question 20

Given N = 1,000, n = 30, and   = 6, the standard error of the sample mean, SE   , equals:

Accepted Answer

A)  .009 
B)  .5 
C)  5.5 
D)  1.095 
E)  33.33 
A)  .009 
B)  .5 
C)  5.5 
D)  1.095 
E)  33.33

Stratified random sampling involves selecting a simple random sample from each of a given number of subpopulations, called strata.

If a sample is selected at random, the main reason that the sample mean might be different than the corresponding population mean is that the sample might be biased.

The sampling distribution of the sample proportion can be approximated by a normal distribution as long as the population proportion p is very close to .50.

As a general rule, the normal distribution provides a good approximation to the sampling distribution of the sample proportion only if:

Small haphazard changes in a process variable due to alteration in the production environment that is not controllable are said to be assignable causes.

When all possible simple random samples of size n are drawn from a population that is normally distributed, the sampling distribution of the sample means will be normal regardless of sample size n.

Twenty five samples of size 1000 each were drawn from a manufacturing process and the number of defectives in each sample was counted. The average sample proportion was 0.05. The upper control limit for the p chart is:

The simple random sample is a subset of a frame, or of an associated population, chosen in such a fashion that every possible subset of like size has an equal chance of being selected.

If random samples of size n = 36 are drawn from a nonnormal population with finite mean and standard deviation , then the sampling distribution of the sample mean is approximately normally distributed with mean and standard deviation

The Central Limit Theorem is used to describe the sampling distributions of statistics, such as and , when the population is known to be normally distributed.

As the sample size increases, the standard error of the sample mean decreases.

If the variation in a process variable is solely random, the process is said to be in control.

A sampling distribution is defined as a sample chosen in such a way that every possible subset of like size has an equal chance of being selected.

If the monthly rent of all one-bedroom apartments in a small town are known to be normally distributed with a mean equal to $175 a month and standard deviation of $35, which of the following would be the highest individual rent that you might expect to find?

Sixty samples of size 600 each were drawn from a manufacturing process and the number of defectives in each sample was counted. The average sample proportion was 0.04. The lower control limit for the p chart is:

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if the sample size n is greater than or equal to 30.

Given N = 1,000, n = 30, and = 6, the standard error of the sample mean, SE , equals:

Describing Data With Graphs

Describing Data With Numerical Measures

Describing Bivariate Data

Probability and Probability Distributions

Several Useful Discrete Distributions

The Normal Probability Distribution

Large-Sample Estimation

Large-Sample Tests of Hypotheses

Inference From Small Samples

The Analysis of Variance

Linear Regression and Correlation

Multiple Regression Analysis

Analysis of Categorical Data

Nonparametric Statistics

Filters

Exam 7: Sampling Distributions

Stratified random sampling involves selecting a simple random sample from each of a given number of subpopulations, called strata.

If a sample is selected at random, the main reason that the sample mean might be different than the corresponding population mean is that the sample might be biased.

The sampling distribution of the sample proportion can be approximated by a normal distribution as long as the population proportion p is very close to .50.

As a general rule, the normal distribution provides a good approximation to the sampling distribution of the sample proportion only if:

Small haphazard changes in a process variable due to alteration in the production environment that is not controllable are said to be assignable causes.

When all possible simple random samples of size n are drawn from a population that is normally distributed, the sampling distribution of the sample means will be normal regardless of sample size n.

Twenty five samples of size 1000 each were drawn from a manufacturing process and the number of defectives in each sample was counted. The average sample proportion was 0.05. The upper control limit for the p chart is:

The simple random sample is a subset of a frame, or of an associated population, chosen in such a fashion that every possible subset of like size has an equal chance of being selected.

If random samples of size n = 36 are drawn from a nonnormal population with finite mean and standard deviation , then the sampling distribution of the sample mean is approximately normally distributed with mean and standard deviation

The Central Limit Theorem is used to describe the sampling distributions of statistics, such as and , when the population is known to be normally distributed.

As the sample size increases, the standard error of the sample mean decreases.

If the variation in a process variable is solely random, the process is said to be in control.

A sampling distribution is defined as a sample chosen in such a way that every possible subset of like size has an equal chance of being selected.

If the monthly rent of all one-bedroom apartments in a small town are known to be normally distributed with a mean equal to $175 a month and standard deviation of $35, which of the following would be the highest individual rent that you might expect to find?

Sixty samples of size 600 each were drawn from a manufacturing process and the number of defectives in each sample was counted. The average sample proportion was 0.04. The lower control limit for the p chart is:

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if the sample size n is greater than or equal to 30.

Given N = 1,000, n = 30, and = 6, the standard error of the sample mean, SE , equals:

Describing Data With Graphs

Describing Data With Numerical Measures

Describing Bivariate Data

Probability and Probability Distributions

Several Useful Discrete Distributions

The Normal Probability Distribution

Large-Sample Estimation

Large-Sample Tests of Hypotheses

Inference From Small Samples

The Analysis of Variance

Linear Regression and Correlation

Multiple Regression Analysis

Analysis of Categorical Data

Nonparametric Statistics

Filters