Question 1

How many independent variables are involved in a multiple regression equation?

Accepted Answer

A) One 
B) Zero 
C) Two or more 
D) At least three 
A) One 
B) Zero 
C) Two or more 
D) At least three

Question 2

SELECT ALL THAT APPLY.
-Covariance

Accepted Answer

A) measures the linear relationship between two variables. 
B) reflects both strength and direction of the relationship. 
C) will be close to zero if the variables are closely related. 
D) will be negative if the relationship is unrelated. 
A) measures the linear relationship between two variables. 
B) reflects both strength and direction of the relationship. 
C) will be close to zero if the variables are closely related. 
D) will be negative if the relationship is unrelated.

Question 3

Which of the following is the equation for all straight-line graphs?

Accepted Answer

A) Y = a + b (x) 
B) e = Y - Ŷ 
C) Ʃ (ӯ - Ŷ) 
D) Ŷ = a (b) 
A) Y = a + b (x) 
B) e = Y - Ŷ 
C) Ʃ (ӯ - Ŷ) 
D) Ŷ = a (b)

Question 4

What is the regression sum of squares?

Accepted Answer

A) The sum of the squared deviations from the mean 
B) The sum of the squared deviations from the regression line 
C) The difference between the sum of the squared deviations from the mean and the sum of the squared deviations from the regression line 
D) The effect of two or more variables on the independent variable 
A) The sum of the squared deviations from the mean 
B) The sum of the squared deviations from the regression line 
C) The difference between the sum of the squared deviations from the mean and the sum of the squared deviations from the regression line 
D) The effect of two or more variables on the independent variable

Question 5

What is the total sum of squares?

Accepted Answer

A) The sum of the squared deviations from the mean 
B) The sum of the squared deviations from the regression line 
C) The difference between the sum of the squared deviations from the mean and the sum of the squared deviations from the regression line 
D) The effect of two or more variables on the independent variable 
A) The sum of the squared deviations from the mean 
B) The sum of the squared deviations from the regression line 
C) The difference between the sum of the squared deviations from the mean and the sum of the squared deviations from the regression line 
D) The effect of two or more variables on the independent variable

Question 6

The following data were obtained from a sample of 12 respondents.Suppose you arrive at the following multiple regression equation which predicts child's schooling from both father and mother's schooling:
Ŷ= 8.91 + .51(Father's Schooling)- .10(Mother's Schooling).
What is the predicted number of years of schooling for a respondent whose father and mother graduated from college (i.e.,each completed 16 years of schooling)?

Accepted Answer

Ŷ = 8.91 +

Question 7

In a linear equation,the value of Y when X is 0 is called the

Accepted Answer

A) slope. 
B) Y-intercept. 
C) best fit. 
D) directional. 
A) slope. 
B) Y-intercept. 
C) best fit. 
D) directional.

Question 8

An $ r^{2} $ near zero indicates either poor fit or a well-fitting line with slope zero.

Accepted Answer

A) True 
 B)False

Question 9

Calculate the Y-intercept,a,of the regression equation using the following information:
Mean number of years of schooling: 17
Mean monthly income: $2,750
Slope,b,of the regression equation: $650

Accepted Answer

The answer of Calculate the Y-intercept,a,of the regression equation using...

Question 10

The covariance between the mean age at childbearing and the total fertility rate is -0.06.How much predictive power does the mean age at childbearing have in predicting the total fertility rate? Calculate the coefficient of determination and interpret this quantity.

Accepted Answer

r2 = 0.18.About 18% of the var

How many independent variables are involved in a multiple regression equation?

SELECT ALL THAT APPLY. -Covariance

Which of the following is the equation for all straight-line graphs?

What is the regression sum of squares?

What is the total sum of squares?

In a linear equation,the value of Y when X is 0 is called the

An $r^{2}$ near zero indicates either poor fit or a well-fitting line with slope zero.

Calculate the Y-intercept,a,of the regression equation using the following information: Mean number of years of schooling: 17 Mean monthly income: $2,750 Slope,b,of the regression equation: $650

The covariance between the mean age at childbearing and the total fertility rate is -0.06.How much predictive power does the mean age at childbearing have in predicting the total fertility rate? Calculate the coefficient of determination and interpret this quantity.

The What and the Why of Statistics

The Organization and Graphic Presentation of Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Sampling and Sampling Distributions

Estimation

Testing Hypotheses

Bivariate Tables

The Chi-Square Test and Measures of Association

Analysis of Variance

Filters

Exam 12: Regression and Correlation

How many independent variables are involved in a multiple regression equation?

SELECT ALL THAT APPLY. -Covariance

Which of the following is the equation for all straight-line graphs?

What is the regression sum of squares?

What is the total sum of squares?

In a linear equation,the value of Y when X is 0 is called the

An r2 r^{2} r2 near zero indicates either poor fit or a well-fitting line with slope zero.

Calculate the Y-intercept,a,of the regression equation using the following information: Mean number of years of schooling: 17 Mean monthly income: $2,750 Slope,b,of the regression equation: $650

The covariance between the mean age at childbearing and the total fertility rate is -0.06.How much predictive power does the mean age at childbearing have in predicting the total fertility rate? Calculate the coefficient of determination and interpret this quantity.

The What and the Why of Statistics

The Organization and Graphic Presentation of Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Sampling and Sampling Distributions

Estimation

Testing Hypotheses

Bivariate Tables

The Chi-Square Test and Measures of Association

Analysis of Variance

Filters

An $r^{2}$ near zero indicates either poor fit or a well-fitting line with slope zero.