Question 1

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is

Accepted Answer

A) 0.4000 
B) 0.0256 
C) 4 
D) 2.56 
A) 0.4000 
B) 0.0256 
C) 4 
D) 2.56

Question 2

Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained.   = 120 - 10 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

Accepted Answer

A) increase by 120 units 
B) increase by 100 units 
C) increase by 20 units 
D) decease by 20 units 
A) increase by 120 units 
B) increase by 100 units 
C) increase by 20 units 
D) decease by 20 units

Question 3

The following sample data contains the number of years of college and the current annual salary for a random sample of heavy equipment salespeople.   
a. Which variable is the dependent variable? Which is the independent variable?
b. Determine the least squares estimated regression line.c. Predict the annual income of a salesperson with one year of college.d. Test if the relationship between years of college and income is statistically significant at the .05 level of significance.e. Calculate the coefficient of determination.
f. Calculate the sample correlation coefficient between income and years of college. Interpret the value you obtain.

Accepted Answer

a.Y (dependent variable) is annual incom

Question 4

The model developed from sample data that has the form of   is known as

Accepted Answer

A) regression equation 
B) correlation equation 
C) estimated regression equation 
D) regression model 
A) regression equation 
B) correlation equation 
C) estimated regression equation 
D) regression model

Question 5

If the coefficient of determination is 0.9, the percentage of variation in the dependent variable explained by the variation in the independent variable

Accepted Answer

A) is 0.90% 
B) is 90%. 
C) is 81% 
D) 0.81% 
A) is 0.90% 
B) is 90%. 
C) is 81% 
D) 0.81%

Question 6

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.   = 500 + 4 X Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is

Accepted Answer

A) $900 
B) $900,000 
C) $40,500 
D) $505,000 
A) $900 
B) $900,000 
C) $40,500 
D) $505,000

Question 7

If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable

Accepted Answer

A) is 40% 
B) is 16%. 
C) is 4% 
D) can be any positive value 
A) is 40% 
B) is 16%. 
C) is 4% 
D) can be any positive value

Question 8

If the coefficient of determination is 0.81, the coefficient of correlation

Accepted Answer

A) is 0.6561 
B) could be either + 0.9 or - 0.9 
C) must be positive 
D) must be negative 
A) is 0.6561 
B) could be either + 0.9 or - 0.9 
C) must be positive 
D) must be negative

Question 9

In a regression and correlation analysis if r2 = 1, then

Accepted Answer

A) SSE = SST 
B) SSE = 1 
C) SSR = SSE 
D) SSR = SST 
A) SSE = SST 
B) SSE = 1 
C) SSR = SSE 
D) SSR = SST

Question 10

If the coefficient of correlation is -0.4, then the slope of the regression line

Accepted Answer

A) must also be -0.4 
B) can be either negative or positive 
C) must be negative 
D) must be 0.16 
A) must also be -0.4 
B) can be either negative or positive 
C) must be negative 
D) must be 0.16

Question 11

Exhibit 14-8
The following information regarding a dependent variable Y and an independent variable X is provided  
-Refer to Exhibit 14-8. The total sum of squares (SST) is

Accepted Answer

A) -156 
B) 234 
C) 1870 
D) 1974 
A) -156 
B) 234 
C) 1870 
D) 1974

Question 12

Exhibit 14-8
The following information regarding a dependent variable Y and an independent variable X is provided  
-Refer to Exhibit 14-8. The slope of the regression equation is

Accepted Answer

A) -0.667 
B) 0.667 
C) 100 
D) -100 
A) -0.667 
B) 0.667 
C) 100 
D) -100

Question 13

Exhibit 14-4
Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained.   = 12 + 1.8 x
n = 17
SSR = 225
SSE = 75
SS1U1B1b1S1U1B0 = 0.2683
-Refer to Exhibit 14-4. The F statistic computed from the above data is

Accepted Answer

A) 3 
B) 45 
C) 48 
D) 50 
A) 3 
B) 45 
C) 48 
D) 50

Question 14

Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

Accepted Answer

The answer of Part of an Excel output relating X...

Question 15

Below you are given information on a woman's age and her annual expenditure on purchase of books.   
a.Develop the least squares regression equation.
b.Compute the coefficient of determination.
c.Use a t test to determine whether the slope is significantly different from zero. Let $\alpha$ = 0.05.
d.At 95% confidence, perform an F test and determine whether or not the model is significant.

Accepted Answer

a. @#IMG-DLM& = 54.834 + 7.536X b.R² = 0.568 c.t =

Question 16

Exhibit 14-8
The following information regarding a dependent variable Y and an independent variable X is provided  
-Refer to Exhibit 14-8. The sum of squares due to error (SSE) is

Accepted Answer

A) -156 
B) 234 
C) 1870 
D) 1974 
A) -156 
B) 234 
C) 1870 
D) 1974

Question 17

Researchers have collected data on the hours of television watched in a day and the age of a person. You are given the data below.   
a.Determine which variable is the dependent variable.
b.Compute the least squares estimated line.
c.Is there a significant relationship between the two variables? Use a .05 level of significance. Be sure to state the null and alternative hypotheses.
d.Compute the coefficient of determination. How would you interpret this value?

Accepted Answer

The answer of Researchers have collected data on the hours...

Question 18

A regression and correlation analysis resulted in the following information regarding an independent variable (x) and a dependent variable (y).
$\Sigma$X = 42
$\Sigma$(Y -   )(X -   ) = 37
$\Sigma$Y = 63
$\Sigma$(X -   )2 = 84
n = 7
$\Sigma$ (Y -   )2 = 28   
a.Develop the least squares estimated regression equation.
b.At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero.
c.Perform an F test to determine whether or not the model is significant. Let $\alpha$ = 0.05.
d.Compute the coefficient of determination.

Accepted Answer

a. @#IMG-DLM& = 6.3571 + 0.440

Question 19

The coefficient of determination

Accepted Answer

A) cannot be negative 
B) is the square root of the coefficient of correlation 
C) is the same as the coefficient of correlation 
D) can be negative or positive 
A) cannot be negative 
B) is the square root of the coefficient of correlation 
C) is the same as the coefficient of correlation 
D) can be negative or positive

Question 20

Exhibit 14-3
You are given the following information about y and x.  
-Refer to Exhibit 14-3. The coefficient of determination equals

Accepted Answer

A) -0.4364 
B) 0.4364 
C) -0.1905 
D) 0.1905 
A) -0.4364 
B) 0.4364 
C) -0.1905 
D) 0.1905

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is

Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. = 120 - 10 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

The model developed from sample data that has the form of is known as

If the coefficient of determination is 0.9, the percentage of variation in the dependent variable explained by the variation in the independent variable

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. = 500 + 4 X Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is

If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable

If the coefficient of determination is 0.81, the coefficient of correlation

In a regression and correlation analysis if r² = 1, then

If the coefficient of correlation is -0.4, then the slope of the regression line

Exhibit 14-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 14-8. The total sum of squares (SST) is

Exhibit 14-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 14-8. The slope of the regression equation is

Exhibit 14-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 S_b1 = 0.2683 -Refer to Exhibit 14-4. The F statistic computed from the above data is

Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

Exhibit 14-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 14-8. The sum of squares due to error (SSE) is

The coefficient of determination

Exhibit 14-3 You are given the following information about y and x. -Refer to Exhibit 14-3. The coefficient of determination equals

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Index Numbers

Decision Analysis on Website

Sample Survey on Website

Filters

Exam 14: Simple Linear Regression

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is

Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. = 120 - 10 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

The model developed from sample data that has the form of is known as

If the coefficient of determination is 0.9, the percentage of variation in the dependent variable explained by the variation in the independent variable

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. = 500 + 4 X Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is

If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable

If the coefficient of determination is 0.81, the coefficient of correlation

In a regression and correlation analysis if r2 = 1, then

If the coefficient of correlation is -0.4, then the slope of the regression line

Exhibit 14-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 14-8. The total sum of squares (SST) is

Exhibit 14-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 14-8. The slope of the regression equation is

Exhibit 14-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 Sb1 = 0.2683 -Refer to Exhibit 14-4. The F statistic computed from the above data is

Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?".

Exhibit 14-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 14-8. The sum of squares due to error (SSE) is

The coefficient of determination

Exhibit 14-3 You are given the following information about y and x. -Refer to Exhibit 14-3. The coefficient of determination equals

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Index Numbers

Decision Analysis on Website

Sample Survey on Website

Filters

In a regression and correlation analysis if r² = 1, then

Exhibit 14-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 S_b1 = 0.2683 -Refer to Exhibit 14-4. The F statistic computed from the above data is