Question 1

Exhibit 12-6
For the following data the value of SSE = 0.4130.
  
-Refer to Exhibit 12-6. The total sum of squares (SST) equals

Accepted Answer

A) 36 
B) 18 
C) 9 
D) 1296 
A) 36 
B) 18 
C) 9 
D) 1296

Question 2

Exhibit 12-10
The following information regarding a dependent variable Y and an independent variable X is provided.  
-Refer to Exhibit 12-10. The coefficient of determination is

Accepted Answer

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

Question 3

Exhibit 12-3
You are given the following information about y and x.
  
-Refer to Exhibit 12-3. The least squares estimate of b0 equals

Accepted Answer

A) 1 
B) -1 
C) -11 
D) 11 
A) 1 
B) -1 
C) -11 
D) 11

Question 4

In a simple regression analysis (where Y is a dependent and X an independent variable), if the Y intercept is positive, then

Accepted Answer

A) there is a positive correlation between X and Y 
B) if X is increased, Y must also increase 
C) if Y is increased, X must also increase 
D) None of these alternatives is correct. 
A) there is a positive correlation between X and Y 
B) if X is increased, Y must also increase 
C) if Y is increased, X must also increase 
D) None of these alternatives is correct.

Question 5

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 6

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.

Question 7

The interval estimate of an individual value of y for a given value of x is

Accepted Answer

A) prediction interval estimate 
B) confidence interval estimate 
C) average regression 
D) x versus y correlation interval 
A) prediction interval estimate 
B) confidence interval estimate 
C) average regression 
D) x versus y correlation interval

Question 8

If the coefficient of correlation is a positive value, then the regression equation

Accepted Answer

A) must have a positive slope 
B) must have a negative slope 
C) could have either a positive or a negative slope 
D) must have a positive y intercept 
A) must have a positive slope 
B) must have a negative slope 
C) could have either a positive or a negative slope 
D) must have a positive y intercept

Question 9

An automobile dealer wants to see if there is a relationship between monthly sales and the interest rate. A random sample of 4 months was taken. The results of the sample are presented below. The estimated least squares regression equation is   = 75.061 - 6.254X
   
a.Obtain a measure of how well the estimated regression line fits the data.
b.You want to test to see if there is a significant relationship between the interest rate and monthly sales at the 1% level of significance. State the null and alternative hypotheses.
c.At 99% confidence, test the hypotheses.
d.Construct a 99% confidence interval for the average monthly sales for all months with a 10% interest rate.
e.
Construct a 99% confidence interval for the monthly sales of one month with a 10% interest rate.

Accepted Answer

a.R² = 0.8687 b.H₀

Question 10

Regression analysis was applied between sales (Y in $1,000) and advertising (X in $100), and the following estimated regression equation was obtained.  = 80 + 6.2 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) $62,080 
B) $142,000 
C) $700 
D) $700,000 
A) $62,080 
B) $142,000 
C) $700 
D) $700,000

Question 11

In a regression analysis, the coefficient of determination is 0.4225. The coefficient of correlation in this situation is

Accepted Answer

A) 0.65 
B) 0.1785 
C) any positive value 
D) any value 
A) 0.65 
B) 0.1785 
C) any positive value 
D) any value

Question 12

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 13

The following data represent the number of flash drives sold per day at a local computer shop and their prices.
   
a.Develop a least-squares regression line and explain what the slope of the line indicates.
b.Compute the coefficient of determination and comment on the strength of relationship between x and y.
c.Compute the sample correlation coefficient between the price and the number of flash drives sold. Use $\alpha$= 0.01 to test the relationship between x and y.

Accepted Answer

a.= 29.7857 - 0.7286x
The slope indicate

Question 14

In the following estimated regression equation

Accepted Answer

A) b1 is the slope 
B) b1 is the intercept 
C) b0 is the slope 
D) None of these alternatives is correct. 
A) b1 is the slope 
B) b1 is the intercept 
C) b0 is the slope 
D) None of these alternatives is correct.

Question 15

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = $\beta$0 + $\beta$1x, 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 16

A regression analysis between demand (Y in 1000 units) and price (X in dollars) resulted in the following equation   = 9 - 3X
The above equation implies that if the price is increased by $1, the demand is expected to

Accepted Answer

A) increase by 6 units 
B) decrease by 3 units 
C) decrease by 6,000 units 
D) decrease by 3,000 units 
A) increase by 6 units 
B) decrease by 3 units 
C) decrease by 6,000 units 
D) decrease by 3,000 units

Question 17

Jason believes that the sales of coffee at his coffee shop depend upon the weather. He has taken a sample of 6 days. Below you are given the results of the sample.
   
a.Which variable is the dependent variable?
b.Compute the least squares estimated line.
c.Compute the correlation coefficient between temperature and the sales of coffee.
d.Is there a significant relationship between the sales of coffee and temperature? Use a .05 level of significance. Be sure to state the null and alternative hypotheses.
e.
Predict sales of a 90 degree day.

Accepted Answer

a.Cups of coffee sold
b.@#IMG-DLM& = 605.714 - 5.9

Question 18

A company has recorded data on the daily demand for its product (Y in thousands of units) and the unit price (X in hundreds of dollars). A sample of 15 days demand and associated prices resulted in the following data.  
a.Using the above information, develop the least-squares estimated regression line and write the equation.
b.Compute the coefficient of determination.
c.Perform an F test and determine whether or not there is a significant relationship between demand and unit price. Let $\alpha$ = 0.05.
d.Would the demand ever reach zero? If yes, at what price would the demand be zero?

Accepted Answer

a.@#IMG-DLM&= 12.138 - 0.6277X b.R² = 0

Question 19

Exhibit 12-8
The following information regarding a dependent variable Y and an independent variable X is provided
  
-Refer to Exhibit 12-8. 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 20

The following data represent the number of flash drives sold per day at a local computer shop and their prices.
   
a.Perform an F test and determine if the price and the number of flash drives sold are related. Let $\alpha$ = 0.01.
b.Perform a t test and determine if the price and the number of flash drives sold are related. Let $\alpha$ = 0.01.

Accepted Answer

a.F = 29.624 > 16.26; p-value < .01; (Ex

Exhibit 12-6 For the following data the value of SSE = 0.4130. -Refer to Exhibit 12-6. The total sum of squares (SST) equals

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The coefficient of determination is

Exhibit 12-3 You are given the following information about y and x. -Refer to Exhibit 12-3. The least squares estimate of b₀ equals

In a simple regression analysis (where Y is a dependent and X an independent variable), if the Y intercept is positive, then

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

The interval estimate of an individual value of y for a given value of x is

If the coefficient of correlation is a positive value, then the regression equation

Regression analysis was applied between sales (Y in $1,000) and advertising (X in $100), and the following estimated regression equation was obtained. = 80 + 6.2 X Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

In a regression analysis, the coefficient of determination is 0.4225. The coefficient of correlation in this situation is

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

In the following estimated regression equation

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = $\beta$ ₀ + $\beta$ ₁x, is known as

A regression analysis between demand (Y in 1000 units) and price (X in dollars) resulted in the following equation = 9 - 3X The above equation implies that if the price is increased by $1, the demand is expected to

Exhibit 12-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 12-8. The slope of the regression equation is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Presentations

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Multiple Regression

Filters

Exam 12: Simple Linear Regression

Exhibit 12-6 For the following data the value of SSE = 0.4130. -Refer to Exhibit 12-6. The total sum of squares (SST) equals

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. -Refer to Exhibit 12-10. The coefficient of determination is

Exhibit 12-3 You are given the following information about y and x. -Refer to Exhibit 12-3. The least squares estimate of b0 equals

In a simple regression analysis (where Y is a dependent and X an independent variable), if the Y intercept is positive, then

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

The interval estimate of an individual value of y for a given value of x is

If the coefficient of correlation is a positive value, then the regression equation

Regression analysis was applied between sales (Y in $1,000) and advertising (X in $100), and the following estimated regression equation was obtained. = 80 + 6.2 X Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

In a regression analysis, the coefficient of determination is 0.4225. The coefficient of correlation in this situation is

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

In the following estimated regression equation

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = β\betaβ 0 + β\betaβ 1x, is known as

A regression analysis between demand (Y in 1000 units) and price (X in dollars) resulted in the following equation = 9 - 3X The above equation implies that if the price is increased by $1, the demand is expected to

Exhibit 12-8 The following information regarding a dependent variable Y and an independent variable X is provided -Refer to Exhibit 12-8. The slope of the regression equation is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Presentations

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Multiple Regression

Filters

Exhibit 12-3 You are given the following information about y and x. -Refer to Exhibit 12-3. The least squares estimate of b₀ equals

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

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = $\beta$ ₀ + $\beta$ ₁x, is known as