Question 1

What are most statistics primarily designed for?

Accepted Answer

A)  to tell us something about error 
B)  to provide the best measurement possible 
C)  to provide estimates of probability 
D)  to predict outcomes 
A)  to tell us something about error 
B)  to provide the best measurement possible 
C)  to provide estimates of probability 
D)  to predict outcomes A

Question 2

Foundation concepts underlying the reason for, and the use of, statistics are:

Accepted Answer

A)  error and variance 
B)  probability and error 
C)  variance and probability 
D)  variance and chance 
A)  error and variance 
B)  probability and error 
C)  variance and probability 
D)  variance and chance A

Question 3

A constant is a variable that always demonstrates a relationship with another variable.

Accepted Answer

A) True 
 B)False  False

Question 4

Inferential statistics are used to establish the accuracy of measurement.

Accepted Answer

A) True 
 B)False

Question 5

Which of the following best describes the concept of "variance"?

Accepted Answer

A)  change is inevitable and all around us 
B)  differences in measurement results 
C)  real fluctuations in measurement 
D)  a and c above 
A)  change is inevitable and all around us 
B)  differences in measurement results 
C)  real fluctuations in measurement 
D)  a and c above

Question 6

Any two identical measurements are sufficient to identify a constant.

Accepted Answer

A) True 
 B)False

Question 7

The robustness of a statistic refers to

Accepted Answer

A)  the ability to be calculated quickly 
B)  the ability to withstand violations of assumptions 
C)  the ability to locate error variance 
D)  the ability to find something that is really there 
A)  the ability to be calculated quickly 
B)  the ability to withstand violations of assumptions 
C)  the ability to locate error variance 
D)  the ability to find something that is really there

Question 8

Descriptive statistics are designed to describe statistical significance of a relationship.

Accepted Answer

A) True 
 B)False

Question 9

Predictive statistics are related to the explanatory phase of knowledge.

Accepted Answer

A) True 
 B)False

Question 10

Estimates of error will always have error in them.

Accepted Answer

A) True 
 B)False

Question 11

A "good" statistic is characterized by which of the following?

Accepted Answer

A)  provides a quick and relatively accurate "picture" of the data 
B)  has the ability to reduce data to the nominal level of measurement 
C)  requires a minimum of calculation 
D)  all of the above 
A)  provides a quick and relatively accurate "picture" of the data 
B)  has the ability to reduce data to the nominal level of measurement 
C)  requires a minimum of calculation 
D)  all of the above

Question 12

There are two basic types of variance. They are:

Accepted Answer

A)  constants and variables 
B)  error variance and real variance 
C)  systematic variance and random variance 
D)  none of the above 
A)  constants and variables 
B)  error variance and real variance 
C)  systematic variance and random variance 
D)  none of the above

Question 13

A constant is best characterized as:

Accepted Answer

A)  a variable that only changes under certain circumstances 
B)  a dependable phenomenon 
C)  unchanging measurement 
D)  the absence of error 
A)  a variable that only changes under certain circumstances 
B)  a dependable phenomenon 
C)  unchanging measurement 
D)  the absence of error

Question 14

Statistics are merely ways to make sense of and understand quantitative information.

Accepted Answer

A) True 
 B)False

Question 15

Chapter 1 in your textbook focuses on:

Accepted Answer

A)  the foundation of statistics 
B)  the application of mathematical formulas 
C)  strategies for studying statistics 
D)  all of the above 
A)  the foundation of statistics 
B)  the application of mathematical formulas 
C)  strategies for studying statistics 
D)  all of the above

Question 16

Predictive statistics measure the strength of a relationship.

Accepted Answer

A) True 
 B)False

Question 17

Before taking a statistics course, everyone has already used statistics. Which of these is (are) an example of these statistics?

Accepted Answer

A)  hash marks 
B)  bar graph 
C)  percentages 
D)  all of the above 
A)  hash marks 
B)  bar graph 
C)  percentages 
D)  all of the above

Question 18

The different statistics we use to tell us about variance and error have different capabilities, particularly in regard to their accuracy and ability to withstand problems in the data.

Accepted Answer

A) True 
 B)False

Question 19

The related concepts of variance and error are the backbone of statistics.

Accepted Answer

A) True 
 B)False

Question 20

Accuracy:

Accepted Answer

A)  is always possible 
B)  always results in larger amounts of variance 
C)  solves all measurement problems 
D)  none of the above 
A)  is always possible 
B)  always results in larger amounts of variance 
C)  solves all measurement problems 
D)  none of the above

What are most statistics primarily designed for?

Foundation concepts underlying the reason for, and the use of, statistics are:

A constant is a variable that always demonstrates a relationship with another variable.

Inferential statistics are used to establish the accuracy of measurement.

Which of the following best describes the concept of "variance"?

Any two identical measurements are sufficient to identify a constant.

The robustness of a statistic refers to

Descriptive statistics are designed to describe statistical significance of a relationship.

Predictive statistics are related to the explanatory phase of knowledge.

Estimates of error will always have error in them.

A "good" statistic is characterized by which of the following?

There are two basic types of variance. They are:

A constant is best characterized as:

Statistics are merely ways to make sense of and understand quantitative information.

Chapter 1 in your textbook focuses on:

Predictive statistics measure the strength of a relationship.

Before taking a statistics course, everyone has already used statistics. Which of these is (are) an example of these statistics?

The different statistics we use to tell us about variance and error have different capabilities, particularly in regard to their accuracy and ability to withstand problems in the data.

The related concepts of variance and error are the backbone of statistics.

Accuracy:

Levels of Measurement

Graphical Statistics

Measures of Central Tendency

Measures of Dispersion

Curves and Distributions

Frequency Distributions

Elementary Relationships: Crosstabulation Tables

Hypotheses and Sampling Distributions

Statistical Significance

Testing for Significance: the Chi-Square Test

Testing for Significance in Two Groups: The T-Test

Testing for Significance in Multiple Groups: The Analysis of Variance Statistic

The Concept of Association

Testing for Association: Phi

Testing for Association: Pearsons R and Regression

Doing Real Research: Elementary Multivariate Relationships

Statistics and Data Analysis

Filters

Exam 1: Introduction to Statistics

What are most statistics primarily designed for?

Foundation concepts underlying the reason for, and the use of, statistics are:

A constant is a variable that always demonstrates a relationship with another variable.

Inferential statistics are used to establish the accuracy of measurement.

Which of the following best describes the concept of "variance"?

Any two identical measurements are sufficient to identify a constant.

The robustness of a statistic refers to

Descriptive statistics are designed to describe statistical significance of a relationship.

Predictive statistics are related to the explanatory phase of knowledge.

Estimates of error will always have error in them.

A "good" statistic is characterized by which of the following?

There are two basic types of variance. They are:

A constant is best characterized as:

Statistics are merely ways to make sense of and understand quantitative information.

Chapter 1 in your textbook focuses on:

Predictive statistics measure the strength of a relationship.

Before taking a statistics course, everyone has already used statistics. Which of these is (are) an example of these statistics?

The different statistics we use to tell us about variance and error have different capabilities, particularly in regard to their accuracy and ability to withstand problems in the data.

The related concepts of variance and error are the backbone of statistics.

Accuracy:

Levels of Measurement

Graphical Statistics

Measures of Central Tendency

Measures of Dispersion

Curves and Distributions

Frequency Distributions

Elementary Relationships: Crosstabulation Tables

Hypotheses and Sampling Distributions

Statistical Significance

Testing for Significance: the Chi-Square Test

Testing for Significance in Two Groups: The T-Test

Testing for Significance in Multiple Groups: The Analysis of Variance Statistic

The Concept of Association

Testing for Association: Phi

Testing for Association: Pearsons R and Regression

Doing Real Research: Elementary Multivariate Relationships

Statistics and Data Analysis

Filters