Question 1

If s X = s Y then r = b Y .

Accepted Answer

A) True 
 B)False

Question 2

The regression constant for predicting Y given X is symbolized by _________.

Accepted Answer

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

Question 3

A researcher collects data on the relationship between the amount of daily exercise an individual gets and the percent body fat of the individual. The following scores are recorded.   If an individual has 22% fat, his predicted amount of daily exercise is _________.

Accepted Answer

A)  22.80 
B)  23.88 
C)  24.76 
D)  20.22 
A)  22.80 
B)  23.88 
C)  24.76 
D)  20.22

Question 4

The assumption of homoscedasticity is that _________.

Accepted Answer

A)  the range of the Y scores is the same as the X scores 
B)  the X and Y distributions have the same mean values 
C)  the variability of Y doesn't change over the X scores 
D)  the variability of the X and Y distributions is the same 
A)  the range of the Y scores is the same as the X scores 
B)  the X and Y distributions have the same mean values 
C)  the variability of Y doesn't change over the X scores 
D)  the variability of the X and Y distributions is the same

Question 5

In regression analysis we are only concerned with perfect as opposed to imperfect relationships.

Accepted Answer

A) True 
 B)False

Question 6

If there is no relationship between the X and Y variables and we desire to predict Y given X using a least-squares criterion, it is best to predict   for every Y score. Is this correct? If so, explain why. (Hint: one of the properties of the mean might be helpful here)

Accepted Answer

The answer of If there is no relationship between the...

Question 7

When predicting Y given X , _________.

Accepted Answer

A)  the prediction is valid only within the range of X 
B)  the variability of the Y values over the range of the X values should be the same 
C)  the representativeness of the sample used to derive the regression line is an important consideration 
D)  all of these 
A)  the prediction is valid only within the range of X 
B)  the variability of the Y values over the range of the X values should be the same 
C)  the representativeness of the sample used to derive the regression line is an important consideration 
D)  all of these

Question 8

S ( Y - Y' ) equals _________.

Accepted Answer

A)  0 
B)  1 
C)  cannot be determined from information given 
D)  who cares 
A)  0 
B)  1 
C)  cannot be determined from information given 
D)  who cares

Question 9

When predicting Y from two variables relative to using only one variable, _________.

Accepted Answer

A)  prediction accuracy always increases 
B)  prediction accuracy is dependent on the relationship between the second variable and the Y variable 
C)  increase in prediction accuracy depends on the correlation between the two predictor variables 
D)  b and c 
A)  prediction accuracy always increases 
B)  prediction accuracy is dependent on the relationship between the second variable and the Y variable 
C)  increase in prediction accuracy depends on the correlation between the two predictor variables 
D)  b and c

Question 10

If b Y is negative, higher values of X are associated with _________.

Accepted Answer

A)  lower values of X' 
B)  higher values of Y 
C)  higher values of ( Y - Y' ) 
D)  lower values of Y 
A)  lower values of X' 
B)  higher values of Y 
C)  higher values of ( Y - Y' ) 
D)  lower values of Y

Question 11

For regression purposes, it is customary to assign Y to the variable we are predicting from.

Accepted Answer

A) True 
 B)False

Question 12

If s Y = s X , then r = b Y .

Accepted Answer

A) True 
 B)False

Question 13

A friend that thinks a lot about statistics asserts that, "the closer the points in the scatter plot are to the least-squares regression line, the higher the correlation." Is your friend correct? Discuss.

Accepted Answer

Your friend is partially correct. The cl

Question 14

The regression of Y on X _________.

Accepted Answer

A)  predicts X given Y 
B)  predicts X ' given X 
C)  predicts Y given X 
D)  predicts Y given Y ' 
A)  predicts X given Y 
B)  predicts X ' given X 
C)  predicts Y given X 
D)  predicts Y given Y '

Question 15

The primary reason we use a scatter plot in linear regression is _________.

Accepted Answer

A)  to determine if the relationship is linear or curvilinear 
B)  to determine the direction of the relationship 
C)  to compute the magnitude of the relationship 
D)  to determine the slope of the least squares regression line 
A)  to determine if the relationship is linear or curvilinear 
B)  to determine the direction of the relationship 
C)  to compute the magnitude of the relationship 
D)  to determine the slope of the least squares regression line

Question 16

Properly speaking, we should limit our predictions to the range of the base data.

Accepted Answer

A) True 
 B)False

Question 17

-If r = 0.4582, s Y = 3.4383, and s X = 5.2165, the value of b Y = _________.

Accepted Answer

A)  0.695 
B)  0.458 
C)  0.302 
D)  1 - 0.458 
E)  none of these 
A)  0.695 
B)  0.458 
C)  0.302 
D)  1 - 0.458 
E)  none of these

Question 18

If   = 0.0 the relationship between the variables is _________.

Accepted Answer

A)  perfect 
B)  imperfect 
C)  curvilinear 
D)  unknown 
A)  perfect 
B)  imperfect 
C)  curvilinear 
D)  unknown

Question 19

The higher the r value, the lower the standard error of estimate.

Accepted Answer

A) True 
 B)False

Question 20

When using more than one predictor variable, _________ tells us the proportion of variance accounted for b y the predictor variables.

Accepted Answer

A)  r 
B)  ΣS X 
C)  ΣS Y 
D)  R 2 
A)  r 
B)  ΣS X 
C)  ΣS Y 
D)  R 2

If s X = s Y then r = b Y .

The regression constant for predicting Y given X is symbolized by _________.

A researcher collects data on the relationship between the amount of daily exercise an individual gets and the percent body fat of the individual. The following scores are recorded. If an individual has 22% fat, his predicted amount of daily exercise is _________.

The assumption of homoscedasticity is that _________.

In regression analysis we are only concerned with perfect as opposed to imperfect relationships.

If there is no relationship between the X and Y variables and we desire to predict Y given X using a least-squares criterion, it is best to predict for every Y score. Is this correct? If so, explain why. (Hint: one of the properties of the mean might be helpful here)

When predicting Y given X , _________.

S ( Y - Y' ) equals _________.

When predicting Y from two variables relative to using only one variable, _________.

If b Y is negative, higher values of X are associated with _________.

For regression purposes, it is customary to assign Y to the variable we are predicting from.

If s Y = s X , then r = b Y .

A friend that thinks a lot about statistics asserts that, "the closer the points in the scatter plot are to the least-squares regression line, the higher the correlation." Is your friend correct? Discuss.

The regression of Y on X _________.

The primary reason we use a scatter plot in linear regression is _________.

Properly speaking, we should limit our predictions to the range of the base data.

-If r = 0.4582, s Y = 3.4383, and s X = 5.2165, the value of b Y = _________.

If = 0.0 the relationship between the variables is _________.

The higher the r value, the lower the standard error of estimate.

When using more than one predictor variable, _________ tells us the proportion of variance accounted for b y the predictor variables.

Statistics and Scientific Method

Basic Mathematical and Measurement Concepts

Frequency Distributions

Measures of Central Tendency and Variability

The Normal Curve and Standard Scores

Correlation

Random Sampling and Probability

Binomial Distribution

Introduction to Hypothesis Testing: Using the Sign Test

Power

Sampling Distributions, Sampling Distribution of the Mean: the Normal Deviate Z Test

Students T Test for Single Samples

Students T Test for Correlated and Independent Groups

Introduction to the Analysis of Variance

Introduction to the Two-Way Analysis of Variance

Chi-Square and Other Nonparametric Tests

Filters

Exam 7: Linear Regression

If s X = s Y then r = b Y .

The regression constant for predicting Y given X is symbolized by _________.

A researcher collects data on the relationship between the amount of daily exercise an individual gets and the percent body fat of the individual. The following scores are recorded. If an individual has 22% fat, his predicted amount of daily exercise is _________.

The assumption of homoscedasticity is that _________.

In regression analysis we are only concerned with perfect as opposed to imperfect relationships.

If there is no relationship between the X and Y variables and we desire to predict Y given X using a least-squares criterion, it is best to predict for every Y score. Is this correct? If so, explain why. (Hint: one of the properties of the mean might be helpful here)

When predicting Y given X , _________.

S ( Y - Y' ) equals _________.

When predicting Y from two variables relative to using only one variable, _________.

If b Y is negative, higher values of X are associated with _________.

For regression purposes, it is customary to assign Y to the variable we are predicting from.

If s Y = s X , then r = b Y .

A friend that thinks a lot about statistics asserts that, "the closer the points in the scatter plot are to the least-squares regression line, the higher the correlation." Is your friend correct? Discuss.

The regression of Y on X _________.

The primary reason we use a scatter plot in linear regression is _________.

Properly speaking, we should limit our predictions to the range of the base data.

-If r = 0.4582, s Y = 3.4383, and s X = 5.2165, the value of b Y = _________.

If = 0.0 the relationship between the variables is _________.

The higher the r value, the lower the standard error of estimate.

When using more than one predictor variable, _________ tells us the proportion of variance accounted for b y the predictor variables.

Statistics and Scientific Method

Basic Mathematical and Measurement Concepts

Frequency Distributions

Measures of Central Tendency and Variability

The Normal Curve and Standard Scores

Correlation

Random Sampling and Probability

Binomial Distribution

Introduction to Hypothesis Testing: Using the Sign Test

Power

Sampling Distributions, Sampling Distribution of the Mean: the Normal Deviate Z Test

Students T Test for Single Samples

Students T Test for Correlated and Independent Groups

Introduction to the Analysis of Variance

Introduction to the Two-Way Analysis of Variance

Chi-Square and Other Nonparametric Tests

Filters