Question 1

The interval estimate of the mean value of y for a given value of x is the

Accepted Answer

A) confidence interval 
B) prediction interval 
C) residual interval 
D) correlation interval 
A) confidence interval 
B) prediction interval 
C) residual interval 
D) correlation interval

Question 2

Exhibit 14-5
You are given the following information about y and x.  
-Refer to Exhibit 14-5. The point estimate of y when x = 10 is

Accepted Answer

A) -10 
B) 10 
C) -4 
D) 4 
A) -10 
B) 10 
C) -4 
D) 4

Question 3

Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be

Accepted Answer

A) narrower 
B) wider 
C) the same 
D) Not enough information is given. 
A) narrower 
B) wider 
C) the same 
D) Not enough information is given.

Question 4

Exhibit 14-5
You are given the following information about y and x.  
-Refer to Exhibit 14-5. The coefficient of determination equals

Accepted Answer

A) 0 
B) -1 
C) +1 
D) -0.5 
A) 0 
B) -1 
C) +1 
D) -0.5

Question 5

Exhibit 14-1
A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x).  
-Refer to Exhibit 14-1. The least squares estimate of b1 equals

Accepted Answer

A) 1 
B) -1 
C) 5.5 
D) 11 
A) 1 
B) -1 
C) 5.5 
D) 11

Question 6

A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation   = 50,000 - 8x The above equation implies that an

Accepted Answer

A) increase of $1 in price is associated with a decrease of $8 in sales 
B) increase of $8 in price is associated with an increase of $8,000 in sales 
C) increase of $1 in price is associated with a decrease of $42,000 in sales 
D) increase of $1 in price is associated with a decrease of $8000 in sales 
A) increase of $1 in price is associated with a decrease of $8 in sales 
B) increase of $8 in price is associated with an increase of $8,000 in sales 
C) increase of $1 in price is associated with a decrease of $42,000 in sales 
D) increase of $1 in price is associated with a decrease of $8000 in sales

Question 7

Exhibit 14-6
You are given the following information about y and x.  
-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 11 days demand and associated price resulted in the following data.   
a.Using the above information, develop the least-squares estimated regression line.
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.Perform a t test to determine whether the slope is significantly different from zero. Let $\alpha$ = 0.05.
e.Would the demand ever reach zero? If yes, at what price would the demand be zero? Show your complete work.

Accepted Answer

a.= 53.502 - 0.893x
b.0.836
c.Since the

Question 8

In regression analysis, the independent variable is

Accepted Answer

A) used to predict other independent variables 
B) used to predict the dependent variable 
C) called the intervening variable 
D) None of these answers is correct. 
A) used to predict other independent variables 
B) used to predict the dependent variable 
C) called the intervening variable 
D) None of these answers is correct.

Question 9

Exhibit 14-6
You are given the following information about y and x.  
-Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable). Use Excel's Regression Tool to construct a residual plot and use it to determine if any model assumption have been violated.

Accepted Answer

@#IMG-DLM& The constant varian

Question 10

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) there is a negative correlation between x and y 
C) if x is increased, y must also increase 
D) None of these answers is correct. 
A) there is a positive correlation between x and y 
B) there is a negative correlation between x and y 
C) if x is increased, y must also increase 
D) None of these answers is correct.

Question 11

In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see

Accepted Answer

A) a horizontal band of points centered near zero 
B) a widening band of points 
C) a band of points having a slope consistent with that of the regression equation 
D) a parabolic band of points 
A) a horizontal band of points centered near zero 
B) a widening band of points 
C) a band of points having a slope consistent with that of the regression equation 
D) a parabolic band of points

Question 12

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

Accepted Answer

A) must also be positive 
B) can be either negative or positive 
C) can be zero 
D) None of these answers is correct. 
A) must also be positive 
B) can be either negative or positive 
C) can be zero 
D) None of these answers is correct.

Question 13

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.   = 500 + 4x Based on the above estimated regression line if advertising is $10,000, 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 14

In a regression analysis if r2 = 1, then

Accepted Answer

A) SSE must also be equal to one 
B) SSE must be equal to zero 
C) SSE can be any positive value 
D) SSE must be negative 
A) SSE must also be equal to one 
B) SSE must be equal to zero 
C) SSE can be any positive value 
D) SSE must be negative

Question 15

Shown below is a portion of a computer output for a regression analysis relating Y (demand) and X (unit price).   
a.Perform a t test and determine whether or not demand and unit price are related. Let $\alpha$ = 0.05.
b.Perform an F test and determine whether or not demand and unit price are related. Let $\alpha$ = 0.05.
c.Compute the coefficient of determination and fully interpret its meaning. Be very specific.
d.Compute the coefficient of correlation and explain the relationship between demand and unit price.

Accepted Answer

a. and b. @#IMG-DLM& @#IMG-DLM& @#IMG-DLM& c.R² = 0.617; 6

Question 16

If two variables, x and y, have a strong linear relationship, then

Accepted Answer

A) there may or may not be any causal relationship between x and y 
B) x causes y to happen 
C) y causes x to happen 
D) None of these answers is correct. 
A) there may or may not be any causal relationship between x and y 
B) x causes y to happen 
C) y causes x to happen 
D) None of these answers is correct.

Question 17

Coyote Cable has been experiencing an increase in cable service subscribers in recent months due to increased advertising and an influx of new residents to the region. The number of subscribers (in 1000's) for the last 16 months are as follows:   Using simple linear regression, forecast the number of subscribers for months 17, 18, 19, and 20.

Accepted Answer

Y = 11.93 + 1.0046X.

Question 18

Larger values of r2 imply that the observations are more closely grouped about the

Accepted Answer

A) average value of the independent variables 
B) average value of the dependent variable 
C) least squares line 
D) origin 
A) average value of the independent variables 
B) average value of the dependent variable 
C) least squares line 
D) origin

Question 19

Exhibit 14-6
You are given the following information about y and x.  
-Refer to Exhibit 14-6. The least squares estimate of b1 equals

Accepted Answer

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

Question 20

Exhibit 14-6
You are given the following information about y and x.  
-A company has recorded data on the weekly sales for its product (y) and the unit price of the competitor's product (x). The data resulting from a random sample of 7 weeks follows. Use Excel's Regression Tool to construct a residual plot and use it to determine if any model assumption have been violated.

Accepted Answer

@#IMG-DLM& The constant varian

The interval estimate of the mean value of y for a given value of x is the

Exhibit 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The point estimate of y when x = 10 is

Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be

Exhibit 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The coefficient of determination equals

Exhibit 14-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 14-1. The least squares estimate of b₁ equals

A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation = 50,000 - 8x The above equation implies that an

In regression analysis, the independent variable is

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

In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see

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

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

In a regression analysis if r² = 1, then

If two variables, x and y, have a strong linear relationship, then

Larger values of r² imply that the observations are more closely grouped about the

Exhibit 14-6 You are given the following information about y and x. -Refer to Exhibit 14-6. The least squares estimate of b₁ 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

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exam 14: Simple Linear Regression

The interval estimate of the mean value of y for a given value of x is the

Exhibit 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The point estimate of y when x = 10 is

Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be

Exhibit 14-5 You are given the following information about y and x. -Refer to Exhibit 14-5. The coefficient of determination equals

Exhibit 14-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 14-1. The least squares estimate of b1 equals

A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation = 50,000 - 8x The above equation implies that an

In regression analysis, the independent variable is

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

In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see

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

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

In a regression analysis if r2 = 1, then

If two variables, x and y, have a strong linear relationship, then

Larger values of r2 imply that the observations are more closely grouped about the

Exhibit 14-6 You are given the following information about y and x. -Refer to Exhibit 14-6. The least squares estimate of b1 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

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exhibit 14-1 A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). -Refer to Exhibit 14-1. The least squares estimate of b₁ equals

In a regression analysis if r² = 1, then

Larger values of r² imply that the observations are more closely grouped about the

Exhibit 14-6 You are given the following information about y and x. -Refer to Exhibit 14-6. The least squares estimate of b₁ equals