Question 1

200 students scored a mean of 500 with a sum of squares of 1000 on the SAT-Verbal test.What is variance estimate?

Accepted Answer

A) 2.242 
B) 2.236 
C) 5.000 
D) 5.025 
A) 2.242 
B) 2.236 
C) 5.000 
D) 5.025

Question 2

Other things being equal,as the population standard deviation becomes larger,the
Standard error of the mean

Accepted Answer

A) becomes smaller 
B) becomes larger 
C) stays the same 
D) sometimes becomes smaller,sometimes becomes larger 
A) becomes smaller 
B) becomes larger 
C) stays the same 
D) sometimes becomes smaller,sometimes becomes larger

Question 3

The sampling distribution of the mean can be generated by drawing random samples of ____ and forming a frequency distribution of all means.

Accepted Answer

A) different sizes 
B) the same size 
C) increasingly larger sizes 
D) none of these 
A) different sizes 
B) the same size 
C) increasingly larger sizes 
D) none of these

Question 4

Given the same population,the sampling distribution of the mean will show _____ than either the sampling distribution of the median or the sampling distribution of the mode.

Accepted Answer

A) greater accuracy 
B) greater variability 
C) less accuracy 
D) less variability 
A) greater accuracy 
B) greater variability 
C) less accuracy 
D) less variability

Question 5

It is virtually impossible for investigators to select truly random samples from very large populations.

Accepted Answer

A) True 
 B)False

Question 6

A third implication of the central limit theorem is that the sampling distribution of the mean can be approximated by a binomial distribution when the sample size is sufficiently large.

Accepted Answer

A) True 
 B)False

Question 7

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 8

The standard error of the mean can be reduced by ___.

Accepted Answer

A) increasing sample size 
B) reducing ó 
C) both a and b 
A) increasing sample size 
B) reducing ó 
C) both a and b

Question 9

The statistics used in most behavioral science disciplines are not applicable to extremely large populations.

Accepted Answer

A) True 
 B)False

Question 10

A(n)____ of a population parameter is one whose average over all possible random samples of a given size equals the value of the parameter.

Accepted Answer

A) estimator 
B) unbiased estimator 
C) biased estimator 
A) estimator 
B) unbiased estimator 
C) biased estimator

Question 11

What is sampling error?

Accepted Answer

The fact that a sample statistic may not

200 students scored a mean of 500 with a sum of squares of 1000 on the SAT-Verbal test.What is variance estimate?

Other things being equal,as the population standard deviation becomes larger,the Standard error of the mean

The sampling distribution of the mean can be generated by drawing random samples of ____ and forming a frequency distribution of all means.

Given the same population,the sampling distribution of the mean will show _____ than either the sampling distribution of the median or the sampling distribution of the mode.

It is virtually impossible for investigators to select truly random samples from very large populations.

A third implication of the central limit theorem is that the sampling distribution of the mean can be approximated by a binomial distribution when the sample size is sufficiently large.

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

The standard error of the mean can be reduced by ___.

The statistics used in most behavioral science disciplines are not applicable to extremely large populations.

A(n)____ of a population parameter is one whose average over all possible random samples of a given size equals the value of the parameter.

What is sampling error?

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

200 students scored a mean of 500 with a sum of squares of 1000 on the SAT-Verbal test.What is variance estimate?

Other things being equal,as the population standard deviation becomes larger,the Standard error of the mean

The sampling distribution of the mean can be generated by drawing random samples of ____ and forming a frequency distribution of all means.

Given the same population,the sampling distribution of the mean will show _____ than either the sampling distribution of the median or the sampling distribution of the mode.

It is virtually impossible for investigators to select truly random samples from very large populations.

A third implication of the central limit theorem is that the sampling distribution of the mean can be approximated by a binomial distribution when the sample size is sufficiently large.

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

The standard error of the mean can be reduced by ___.

The statistics used in most behavioral science disciplines are not applicable to extremely large populations.

A(n)____ of a population parameter is one whose average over all possible random samples of a given size equals the value of the parameter.

What is sampling error?

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