Question 1

In a scatterplot, an outlier is one that

Accepted Answer

A)  is far to the left of the display. 
B)  is in the center of the display. 
C)  is far from the regression line. 
D)  is the largest value of Y . 
A)  is far to the left of the display. 
B)  is in the center of the display. 
C)  is far from the regression line. 
D)  is the largest value of Y . C

Question 2

-Calculate SSerror for the previous data. Explain how you did it.

Accepted Answer

SS _error = 170.6. I calculated it by summing the square of each residual. (See above table)

Question 3

Given the following data, do you believe the regression equation would be a reliable way to predict values of Y. Explain your answer.

Accepted Answer

No. From looking at the graph, the line of best fit is not very fitting at all. There are large deviations between the line of best fit and many individual points on the line. Further, the regression line is practically flat, suggesting the association between X and Y is not different from 0. It would be unwise to predict Y from a variable that is not related to it. This would be no better than just guessing.

Question 4

In calculating the regression coefficients we square the errors of prediction because

Accepted Answer

A)  statisticians square everything. 
B)  the sum of the errors would always be 0 for a great many lines we could draw. 
C)  squaring makes the errors more striking. 
D)  little errors are more important than big errors. 
A)  statisticians square everything. 
B)  the sum of the errors would always be 0 for a great many lines we could draw. 
C)  squaring makes the errors more striking. 
D)  little errors are more important than big errors.

Question 5

The notation ( Y - Ŷ ) represents

Accepted Answer

A)  our best prediction. 
B)  the regression line. 
C)  the predicted value. 
D)  error in prediction. 
A)  our best prediction. 
B)  the regression line. 
C)  the predicted value. 
D)  error in prediction.

Question 6

If you want to plot the regression line, after having found the regression equation, you need to calculate Ŷ  for _______ value(s) of X .

Accepted Answer

A)  all possible 
B)  one 
C)  a minimum of two 
D)  at least five 
A)  all possible 
B)  one 
C)  a minimum of two 
D)  at least five

Question 7

If the slope is significant we know that

Accepted Answer

A)  the intercept is not significant. 
B)  the intercept is significant. 
C)  there is a strong relationship between the two variables. 
D)  none of the above 
A)  the intercept is not significant. 
B)  the intercept is significant. 
C)  there is a strong relationship between the two variables. 
D)  none of the above

Question 8

When there is only one predictor variable in a regression, beta (regression coefficient) = r (correlation coefficient).

Accepted Answer

A) True 
 B)False

Question 9

The equation for a straight line is an equation of the form

Accepted Answer

A)  Y = bX × a 
B)  Y = bX 
C)  Y = bX 2 + a 
D)  Y = bX + a 
A)  Y = bX × a 
B)  Y = bX 
C)  Y = bX 2 + a 
D)  Y = bX + a

Question 10

When we use a regression equation to make a prediction, the errors that we make are often referred to as

Accepted Answer

A)  residuals. 
B)  predictions. 
C)  Ŷ 
D)  standard errors. 
A)  residuals. 
B)  predictions. 
C)  Ŷ 
D)  standard errors.

Question 11

Regression is only appropriate for predicting a criterion variable from one predictor variable.

Accepted Answer

A) True 
 B)False

Question 12

An example in the text hypothesized that 4% of the variability in life expectancy was accounted for by variability in smoking behavior. The values of r and r2 , respectively, are equal to

Accepted Answer

A)  .20 and .04. 
B)  .04 and .16. 
C)  .04 and .20. 
D)  More information is needed. 
A)  .20 and .04. 
B)  .04 and .16. 
C)  .04 and .20. 
D)  More information is needed.

Question 13

Given this regression equation, Ŷ = .75 X + 5, estimate Y for the following values of X. 
a. X = 0 
b. X = 1 
c. X = -3 
d. X = 75

Accepted Answer

a. 5 
b. 5

Question 14

Answer the following questions based on the regression data in the previous table. 
a. What percent of variability in behavior problems is accounted for by anger? 
b. What percent of variability in behavior problems independent of anger?

Accepted Answer

a. .20 (.448² since b

Question 15

In the equation for a straight line used in the text, the slope is represented by

Accepted Answer

A)  a 
B)  b 
C)  X 
D)  Y 
A)  a 
B)  b 
C)  X 
D)  Y

Question 16

If we do know X , our measure of error is

Accepted Answer

A)  the standard deviation of Y. 
B)  the standard deviation of X. 
C)  the standard error of estimate. 
D)  the standardized residual. 
A)  the standard deviation of Y. 
B)  the standard deviation of X. 
C)  the standard error of estimate. 
D)  the standardized residual.

Question 17

If we want to specify the percentage of the overall variability in life expectancy attributable to variability in smoking behavior, the statistic we want to look at is

Accepted Answer

A)  r 
B)  r2 
C)  b 
D)    
A)  r 
B)  r2 
C)  b 
D)

Question 18

If the correlation between a body image measure and an eating disorders measure is .50, we can conclude that

Accepted Answer

A)  body image has very little to do with eating disorders. 
B)  50% of the variability in the eating disorders scales is associated with variability in body image. 
C)  one quarter of the variability in the eating disorders scores is associated with variability in body image. 
D)  overweight people eat too much. 
A)  body image has very little to do with eating disorders. 
B)  50% of the variability in the eating disorders scales is associated with variability in body image. 
C)  one quarter of the variability in the eating disorders scores is associated with variability in body image. 
D)  overweight people eat too much.

Question 19

Which of the following does NOT belong with the rest?

Accepted Answer

A)  variance attributable to 
B)  variance associated with 
C)  variance predictable from 
D)  variance caused by 
A)  variance attributable to 
B)  variance associated with 
C)  variance predictable from 
D)  variance caused by

Question 20

When we make a prediction using a regression equation, our prediction is _______ on X .

Accepted Answer

A)  dependent 
B)  conditional 
C)  correlated 
D)  both a and b 
A)  dependent 
B)  conditional 
C)  correlated 
D)  both a and b

Exam 10: Regression

In a scatterplot, an outlier is one that

-Calculate SSerror for the previous data. Explain how you did it.

Given the following data, do you believe the regression equation would be a reliable way to predict values of Y. Explain your answer.

In calculating the regression coefficients we square the errors of prediction because

The notation ( Y - Ŷ ) represents

If you want to plot the regression line, after having found the regression equation, you need to calculate Ŷ for _______ value(s) of X .

If the slope is significant we know that

When there is only one predictor variable in a regression, beta (regression coefficient) = r (correlation coefficient).

The equation for a straight line is an equation of the form

When we use a regression equation to make a prediction, the errors that we make are often referred to as

Regression is only appropriate for predicting a criterion variable from one predictor variable.

An example in the text hypothesized that 4% of the variability in life expectancy was accounted for by variability in smoking behavior. The values of r and r2 , respectively, are equal to

Given this regression equation, Ŷ = .75 X + 5, estimate Y for the following values of X. a. X = 0 b. X = 1 c. X = -3 d. X = 75

Answer the following questions based on the regression data in the previous table. a. What percent of variability in behavior problems is accounted for by anger? b. What percent of variability in behavior problems independent of anger?

In the equation for a straight line used in the text, the slope is represented by

If we do know X , our measure of error is

If we want to specify the percentage of the overall variability in life expectancy attributable to variability in smoking behavior, the statistic we want to look at is

If the correlation between a body image measure and an eating disorders measure is .50, we can conclude that

Which of the following does NOT belong with the rest?

When we make a prediction using a regression equation, our prediction is _______ on X .

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Multiple Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

-Calculate SS_error for the previous data. Explain how you did it.

An example in the text hypothesized that 4% of the variability in life expectancy was accounted for by variability in smoking behavior. The values of r and r² , respectively, are equal to