Question 1

Your best guess of the true population variance is the ___.

Accepted Answer

A) sample variance 
B) SS/N 
C) variance estimate 
D)   
2 
A) sample variance 
B) SS/N 
C) variance estimate 
D)   
2

Question 2

In what way is the sample variance a biased estimator of the population variance and how do we correct for this bias?

Accepted Answer

Statisticians have determined that the s

Question 3

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 4

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 5

There is a different sampling distribution of the mean for every sample size.

Accepted Answer

A) True 
 B)False

Question 6

There is a difference sampling distribution for every sample size.

Accepted Answer

A) True 
 B)False

Question 7

The standard error of the mean _____.

Accepted Answer

A) is the standard deviation of the sampling distribution of the mean 
B) is the "average" amount of sampling error across all random samples of a given size 
C) decreases as sample size (N)increases,all other things being equal 
D) all of these 
A) is the standard deviation of the sampling distribution of the mean 
B) is the "average" amount of sampling error across all random samples of a given size 
C) decreases as sample size (N)increases,all other things being equal 
D) all of these

Question 8

When attempting to estimate a population parameter from a small sample,____ occurs.

Accepted Answer

A) experimenter bias 
B) distribution error 
C) sampling error 
D) no error 
A) experimenter bias 
B) distribution error 
C) sampling error 
D) no error

Question 9

An unbiased estimate of the population variance can be obtained by dividing the sample sum of squares by N - 1.

Accepted Answer

A) True 
 B)False

Question 10

If you were to select a sample size that included the entire set of population scores,then the standard deviation of the sampling distribution based on that N would always equal ____.

Accepted Answer

A) 1.00 
B) ó 
C) 0 
D) ó2 
A) 1.00 
B) ó 
C) 0 
D) ó2

Question 11

The standard error of the mean reflects the accuracy with which _____ estimate a _____.

Accepted Answer

A) sample means;population mean 
B) sample variances;population variance 
C) samples;population 
D) standard deviations;standard error 
A) sample means;population mean 
B) sample variances;population variance 
C) samples;population 
D) standard deviations;standard error

Question 12

In general,estimation of a population parameter becomes more accurate as ____.

Accepted Answer

A) df of the sample increases 
B) df of the sample decreases 
C) population size increases 
D) none of these 
A) df of the sample increases 
B) df of the sample decreases 
C) population size increases 
D) none of these

Question 13

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 14

The formula for calculating the standard deviation of a sampling distribution of the mean is ____.

Accepted Answer

A) SS/N - 1 
B) ó2/N 
C) ó/   
D) ó2/   
A) SS/N - 1 
B) ó2/N 
C) ó/   
D) ó2/

Question 15

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 16

To estimate the standard error of the mean we use___.

Accepted Answer

A) s 
B) s2/   
C) s/   
D) none of these 
A) s 
B) s2/   
C) s/   
D) none of these

Question 17

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 18

As degrees of freedom for a statistic increase,the more accurate the estimate of the ____________________ value will be.

Accepted Answer

The answer of As degrees of freedom for a statistic...

Question 19

A _____ can be formally defined as a theoretical distribution consisting of the mean scores for all possible random samples of a given size that could be drawn from a population.

Accepted Answer

A) sampling distribution of the mean 
B) sampling distribution of the sample 
C) sampling distribution of the scores 
D) none of these 
A) sampling distribution of the mean 
B) sampling distribution of the sample 
C) sampling distribution of the scores 
D) none of these

Question 20

Which of the following formulas for the variance would be used if a researcher is interested in inferring what the population value would be?

Accepted Answer

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

Your best guess of the true population variance is the ___.

In what way is the sample variance a biased estimator of the population variance and how do we correct for this bias?

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.

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.

There is a different sampling distribution of the mean for every sample size.

There is a difference sampling distribution for every sample size.

The standard error of the mean _____.

When attempting to estimate a population parameter from a small sample,____ occurs.

An unbiased estimate of the population variance can be obtained by dividing the sample sum of squares by N - 1.

If you were to select a sample size that included the entire set of population scores,then the standard deviation of the sampling distribution based on that N would always equal ____.

The standard error of the mean reflects the accuracy with which _ estimate a _.

In general,estimation of a population parameter becomes more accurate as ____.

The standard deviation of the sampling distribution of the mean is

The formula for calculating the standard deviation of a sampling distribution of the mean is ____.

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

To estimate the standard error of the mean we use___.

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

As degrees of freedom for a statistic increase,the more accurate the estimate of the ____________________ value will be.

A _____ can be formally defined as a theoretical distribution consisting of the mean scores for all possible random samples of a given size that could be drawn from a population.

Which of the following formulas for the variance would be used if a researcher is interested in inferring what the population value would be?

Introduction and Mathematical Preliminaries

Frequency and Probability Distributions

Percentiles percentile Ranks standard Scores and the Normal Distribution

Pearson Correlation and Regression: Descriptive Aspects

Measures of Central Tendency and Variability

Hypothesis Testing: Inferences About a Single Mean

Probability

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

Your best guess of the true population variance is the ___.

In what way is the sample variance a biased estimator of the population variance and how do we correct for this bias?

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.

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.

There is a different sampling distribution of the mean for every sample size.

There is a difference sampling distribution for every sample size.

The standard error of the mean _____.

When attempting to estimate a population parameter from a small sample,____ occurs.

An unbiased estimate of the population variance can be obtained by dividing the sample sum of squares by N - 1.

If you were to select a sample size that included the entire set of population scores,then the standard deviation of the sampling distribution based on that N would always equal ____.

The standard error of the mean reflects the accuracy with which _____ estimate a _____.

In general,estimation of a population parameter becomes more accurate as ____.

The standard deviation of the sampling distribution of the mean is

The formula for calculating the standard deviation of a sampling distribution of the mean is ____.

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

To estimate the standard error of the mean we use___.

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

As degrees of freedom for a statistic increase,the more accurate the estimate of the ____________________ value will be.

A _____ can be formally defined as a theoretical distribution consisting of the mean scores for all possible random samples of a given size that could be drawn from a population.

Which of the following formulas for the variance would be used if a researcher is interested in inferring what the population value would be?

Introduction and Mathematical Preliminaries

Frequency and Probability Distributions

Percentiles percentile Ranks standard Scores and the Normal Distribution

Pearson Correlation and Regression: Descriptive Aspects

Measures of Central Tendency and Variability

Hypothesis Testing: Inferences About a Single Mean

Probability

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.

The standard error of the mean reflects the accuracy with which _ estimate a _.