Question 1

The square root of the variance is the.

Accepted Answer

A) standard deviation 
B) range 
C) median 
D) mode 
A) standard deviation 
B) range 
C) median 
D) mode

Question 2

The population standard deviation is defined as the.

Accepted Answer

A) population variance divided by the size of the population 
B) population variance divided by the size of the population minus one 
C) square root of the population variance 
D) population variance squared 
A) population variance divided by the size of the population 
B) population variance divided by the size of the population minus one 
C) square root of the population variance 
D) population variance squared

Question 3

If a standard deviation for a set of scores is 4.0, then the variance for those scores is.

Accepted Answer

A) 2.0 
B) 4.0 
C) 8.0 
D) none of the above 
A) 2.0 
B) 4.0 
C) 8.0 
D) none of the above

Question 4

If a distribution of scores is approximately symmetrical, then the and are the preferred descriptive statistics.

Accepted Answer

A) median; range 
B) median; mean 
C) mean; variance 
D) mean; standard deviation 
A) median; range 
B) median; mean 
C) mean; variance 
D) mean; standard deviation

Question 5

The choice of a measure of variability to describe scores is determined by which of the following?

Accepted Answer

A) The scale of measurement. 
B) The shape of the frequency distribution. 
C) The intended further statistical analysis of the data. 
D) All the above. 
A) The scale of measurement. 
B) The shape of the frequency distribution. 
C) The intended further statistical analysis of the data. 
D) All the above.

Question 6

The population variance is represented by.

Accepted Answer

A)  $S ^ { 2 }$ 
B)  $s ^ { 2 }$ 
C)  $\sigma$ 
D)  $\sigma ^ { 2 }$ 
A)  $S ^ { 2 }$ 
B)  $s ^ { 2 }$ 
C)  $\sigma$ 
D)  $\sigma ^ { 2 }$

Question 7

The square root of the population variance is the population.

Accepted Answer

A) range 
B) standard deviation 
C) median 
D) mode 
A) range 
B) standard deviation 
C) median 
D) mode

Question 8

Which of the following measures of variability includes 100 percent of the scores in a distribution?

Accepted Answer

A) range 
B) variance 
C) parameter 
D) standard deviation 
A) range 
B) variance 
C) parameter 
D) standard deviation

Question 9

The estimated population variance is defined as the sum of the.

Accepted Answer

A) squared differences of each score from the mean of a distribution divided by the sample size 
B) differences of each score from the mean of a distribution divided by the sample size 
C) squared differences of each score from the mean of a distribution divided by the sample size minus one 
D) differences of each score from the mean of a distribution divided by the sample size minus one 
A) squared differences of each score from the mean of a distribution divided by the sample size 
B) differences of each score from the mean of a distribution divided by the sample size 
C) squared differences of each score from the mean of a distribution divided by the sample size minus one 
D) differences of each score from the mean of a distribution divided by the sample size minus one

Question 10

If the appropriate measure of central tendency is the mean, then the most appropriate measure of variability is the.

Accepted Answer

A) median 
B) range 
C) standard deviation 
D) population variance 
A) median 
B) range 
C) standard deviation 
D) population variance

Question 11

The choice of a measure of variability to describe scores is not determined by which of the following?

Accepted Answer

A) The scale of measurement. 
B) The size of the class interval. 
C) The shape of the frequency distribution. 
D) The intended further statistical analysis of the data. 
A) The scale of measurement. 
B) The size of the class interval. 
C) The shape of the frequency distribution. 
D) The intended further statistical analysis of the data.

Question 12

represents the formula for the.

Accepted Answer

A) sample variance 
B) estimated population variance 
C) sample standard deviation 
D) estimated population standard deviation 
A) sample variance 
B) estimated population variance 
C) sample standard deviation 
D) estimated population standard deviation

Question 13

The population variance is defined as the sum of the.

Accepted Answer

A) squared differences of each score from the sample mean of a distribution divided by the sample size 
B) differences of each score from the mean of a population divided by the population size 
C) squared differences of each score from the mean of a population divided by the population size 
D) differences of each score from the mean of a population divided by the population size minus one 
A) squared differences of each score from the sample mean of a distribution divided by the sample size 
B) differences of each score from the mean of a population divided by the population size 
C) squared differences of each score from the mean of a population divided by the population size 
D) differences of each score from the mean of a population divided by the population size minus one

The square root of the variance is the.

The population standard deviation is defined as the.

If a standard deviation for a set of scores is 4.0, then the variance for those scores is.

If a distribution of scores is approximately symmetrical, then the and are the preferred descriptive statistics.

The choice of a measure of variability to describe scores is determined by which of the following?

The population variance is represented by.

The square root of the population variance is the population.

Which of the following measures of variability includes 100 percent of the scores in a distribution?

The estimated population variance is defined as the sum of the.

If the appropriate measure of central tendency is the mean, then the most appropriate measure of variability is the.

The choice of a measure of variability to describe scores is not determined by which of the following?

represents the formula for the.

The population variance is defined as the sum of the.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

One-Factor Between-Subjects Analysis of Variance

Two-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters

Exam 5: Looking at Data: Measures of Variability

The square root of the variance is the.

The population standard deviation is defined as the.

If a standard deviation for a set of scores is 4.0, then the variance for those scores is.

If a distribution of scores is approximately symmetrical, then the and are the preferred descriptive statistics.

The choice of a measure of variability to describe scores is determined by which of the following?

The population variance is represented by.

The square root of the population variance is the population.

Which of the following measures of variability includes 100 percent of the scores in a distribution?

The estimated population variance is defined as the sum of the.

If the appropriate measure of central tendency is the mean, then the most appropriate measure of variability is the.

The choice of a measure of variability to describe scores is not determined by which of the following?

represents the formula for the.

The population variance is defined as the sum of the.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

One-Factor Between-Subjects Analysis of Variance

Two-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters