Question 1

The sample variance,on average,____the true population variance.

Accepted Answer

A) always equals 
B) overestimates 
C) underestimates 
D) none of these 
A) always equals 
B) overestimates 
C) underestimates 
D) none of these

Question 2

If you were provided a set of 8 scores,____ would correspond to the degrees of freedom associated with the sum of squares of the 8 scores.

Accepted Answer

A) 7 
B) 8 
C) 6 
D) none of these 
A) 7 
B) 8 
C) 6 
D) none of these

Question 3

The sample variance overestimates (is larger than)the population variance across all possible samples of a given size.

Accepted Answer

A) True 
 B)False

Question 4

By far the most common occurrence in the behavioral sciences involves the estimation of population parameters from sample data.

Accepted Answer

A) True 
 B)False

Question 5

In practice,it is possible to compute the exact amount of sampling error that occurs.

Accepted Answer

A) True 
 B)False

Question 6

Which of the following statistics can we use to create sampling distributions?

Accepted Answer

A) mean 
B) median 
C) variance 
D) all of these 
A) mean 
B) median 
C) variance 
D) all of these

Question 7

The fact that a sample statistic may not equal the value of its corresponding population parameter is said to be the result of:

Accepted Answer

A) sampling error 
B) systematic error 
C) random error 
D) parametric error 
A) sampling error 
B) systematic error 
C) random error 
D) parametric error

Question 8

According to the central limit theorem,what is the relationship between the sampling distribution of the mean and the normal distribution?

Accepted Answer

According to the central limit theorem,t

Question 9

One result of the central limit theorem is that the mean of a sampling distribution of the mean is never equal to the population mean.

Accepted Answer

A) True 
 B)False

Question 10

The sample mean is a(n)_____ estimator of the population mean because it _____ the population mean across all possible random samples of a given size.

Accepted Answer

A) biased;underestimates 
B) biased;overestimates 
C) unbiased;equals 
D) unbiased;underestimates 
A) biased;underestimates 
B) biased;overestimates 
C) unbiased;equals 
D) unbiased;underestimates

Question 11

In practice,we always calculate a sampling distribution of the mean.

Accepted Answer

A) True 
 B)False

Question 12

When the degrees of freedom are greater than 40,the normal approximation of the sampling distribution of the mean is quite good.

Accepted Answer

A) True 
 B)False

Question 13

According to the central limit theorem,the mean of the sampling distribution ____ the mean of the population.

Accepted Answer

A) is somewhat less than 
B) is slightly greater than 
C) greatly underestimates 
D) is always equal to 
A) is somewhat less than 
B) is slightly greater than 
C) greatly underestimates 
D) is always equal to

Question 14

An unbiased estimator is a statistic whose mean across all possible random samples of a given size equals the value of the ____________________ parameter.

Accepted Answer

The answer of An unbiased estimator is a statistic whose...

Question 15

Which of the following formulas for the mean would be used if a researcher is only interested in describing a sample without making inferences to a population?

Accepted Answer

A)    
B)    
C)    
D)    
A)    
B)    
C)    
D)

Question 16

What is an unbiased estimator?

Accepted Answer

An unbiased estimator of a population pa

Question 17

The standard deviation of the sampling distribution of the mean is

Accepted Answer

A) the standard deviation of the mean. 
B) the standard error of the mean. 
C) the sampling distribution of the standard deviation. 
D) the population standard deviation. 
A) the standard deviation of the mean. 
B) the standard error of the mean. 
C) the sampling distribution of the standard deviation. 
D) the population standard deviation.

Question 18

An unbiased estimator of the population variance cannot be obtained from sample data.

Accepted Answer

A) True 
 B)False

Question 19

Statisticians have determined that the sample variance is a(n)_____ estimator of the population variance in that it _____ the population variance across all possible random samples of a given size.

Accepted Answer

A) unbiased;accurately estimates 
B) unbiased;overestimates 
C) biased;overestimates 
D) biased;underestimates 
A) unbiased;accurately estimates 
B) unbiased;overestimates 
C) biased;overestimates 
D) biased;underestimates

Question 20

Which of the following situations is most likely to produce a random sample?

Accepted Answer

A) a selection procedure that reduces the chances of selecting improbable events 
B) balancing the sample with both improbable and probable elements of the population 
C) a selection procedure devised so that each element in the population is equally likely to be selected 
D) all of these 
A) a selection procedure that reduces the chances of selecting improbable events 
B) balancing the sample with both improbable and probable elements of the population 
C) a selection procedure devised so that each element in the population is equally likely to be selected 
D) all of these

The sample variance,on average,____the true population variance.

If you were provided a set of 8 scores,____ would correspond to the degrees of freedom associated with the sum of squares of the 8 scores.

The sample variance overestimates (is larger than)the population variance across all possible samples of a given size.

By far the most common occurrence in the behavioral sciences involves the estimation of population parameters from sample data.

In practice,it is possible to compute the exact amount of sampling error that occurs.

Which of the following statistics can we use to create sampling distributions?

The fact that a sample statistic may not equal the value of its corresponding population parameter is said to be the result of:

According to the central limit theorem,what is the relationship between the sampling distribution of the mean and the normal distribution?

One result of the central limit theorem is that the mean of a sampling distribution of the mean is never equal to the population mean.

The sample mean is a(n)_ estimator of the population mean because it _ the population mean across all possible random samples of a given size.

In practice,we always calculate a sampling distribution of the mean.

When the degrees of freedom are greater than 40,the normal approximation of the sampling distribution of the mean is quite good.

According to the central limit theorem,the mean of the sampling distribution ____ the mean of the population.

An unbiased estimator is a statistic whose mean across all possible random samples of a given size equals the value of the ____________________ parameter.

Which of the following formulas for the mean would be used if a researcher is only interested in describing a sample without making inferences to a population?

What is an unbiased estimator?

The standard deviation of the sampling distribution of the mean is

An unbiased estimator of the population variance cannot be obtained from sample data.

Statisticians have determined that the sample variance is a(n)_ estimator of the population variance in that it _ the population variance across all possible random samples of a given size.

Which of the following situations is most likely to produce a random sample?

Introduction and Mathematical Preliminaries

Frequency and Probability Distributions

Measures of Central Tendency and Variability

Percentiles,percentile Ranks,standard Scores,and the Normal Distribution

Pearson Correlation and Regression: Descriptive Aspects

Probability

Hypothesis Testing: Inferences About a Single Mean

Principles of Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships

Independent Groups T-Test

Correlated Groups T-Test

One-Way Repeated Measures Analysis of Variance

Pearson Correlation and Regression: Inferential Aspects

Chi-Square Test

Nonparametric Statistics

Two-Way Between-Subjects Analysis of Variance

Overview and Extension: Statistical Tests for More Complex Designs

Filters

Exam 7: Estimation and Sampling Distributions

The sample variance,on average,____the true population variance.

If you were provided a set of 8 scores,____ would correspond to the degrees of freedom associated with the sum of squares of the 8 scores.

The sample variance overestimates (is larger than)the population variance across all possible samples of a given size.

By far the most common occurrence in the behavioral sciences involves the estimation of population parameters from sample data.

In practice,it is possible to compute the exact amount of sampling error that occurs.

Which of the following statistics can we use to create sampling distributions?

The fact that a sample statistic may not equal the value of its corresponding population parameter is said to be the result of:

According to the central limit theorem,what is the relationship between the sampling distribution of the mean and the normal distribution?

One result of the central limit theorem is that the mean of a sampling distribution of the mean is never equal to the population mean.

The sample mean is a(n)_____ estimator of the population mean because it _____ the population mean across all possible random samples of a given size.

In practice,we always calculate a sampling distribution of the mean.

When the degrees of freedom are greater than 40,the normal approximation of the sampling distribution of the mean is quite good.

According to the central limit theorem,the mean of the sampling distribution ____ the mean of the population.

An unbiased estimator is a statistic whose mean across all possible random samples of a given size equals the value of the ____________________ parameter.

Which of the following formulas for the mean would be used if a researcher is only interested in describing a sample without making inferences to a population?

What is an unbiased estimator?

The standard deviation of the sampling distribution of the mean is

An unbiased estimator of the population variance cannot be obtained from sample data.

Statisticians have determined that the sample variance is a(n)_____ estimator of the population variance in that it _____ the population variance across all possible random samples of a given size.

Which of the following situations is most likely to produce a random sample?

Introduction and Mathematical Preliminaries

Frequency and Probability Distributions

Measures of Central Tendency and Variability

Percentiles,percentile Ranks,standard Scores,and the Normal Distribution

Pearson Correlation and Regression: Descriptive Aspects

Probability

Hypothesis Testing: Inferences About a Single Mean

Principles of Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships

Independent Groups T-Test

Correlated Groups T-Test

One-Way Repeated Measures Analysis of Variance

Pearson Correlation and Regression: Inferential Aspects

Chi-Square Test

Nonparametric Statistics

Two-Way Between-Subjects Analysis of Variance

Overview and Extension: Statistical Tests for More Complex Designs

Filters

The sample mean is a(n)_ estimator of the population mean because it _ the population mean across all possible random samples of a given size.

Statisticians have determined that the sample variance is a(n)_ estimator of the population variance in that it _ the population variance across all possible random samples of a given size.