Question 1

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed

Accepted Answer

A) True 
 B)False

Question 2

The following data is to be used to construct a regression model:   The regression equation is ___.

Accepted Answer

A)  y = 16.49 + 1.43x 
B)  y = 1.19 + 0.91x 
C)  y = 1.19 + 0.75x 
D)  y = 0.75 + 0.18x 
E)  y = 0.91 + 4.06x 
A)  y = 16.49 + 1.43x 
B)  y = 1.19 + 0.91x 
C)  y = 1.19 + 0.75x 
D)  y = 0.75 + 0.18x 
E)  y = 0.91 + 4.06x

Question 3

In the regression equation, y=2.164+1.3657x, n=6, the mean of x is 8.667, Sxx=89.333 and Se=3.44. A 95% prediction interval for y when x = 8 is ___.

Accepted Answer

A)  (9.13, 17.05) 
B)  (2.75, 23.43) 
C)  (10.31, 15.86) 
D)  (3.56, 22.62) 
E)  (12.09, 14.09) 
A)  (9.13, 17.05) 
B)  (2.75, 23.43) 
C)  (10.31, 15.86) 
D)  (3.56, 22.62) 
E)  (12.09, 14.09)

Question 4

The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be ___.

Accepted Answer

A)  0.6 
B)  -0.6 or +0.6 
C)  0.13 
D)  -0.36 
E)  0.36 
A)  0.6 
B)  -0.6 or +0.6 
C)  0.13 
D)  -0.36 
E)  0.36

Question 5

Abby Kratz, a market specialist at the market research firm of Saez, Sikes, and Spitz, is analyzing household budget data collected by her firm. Abby's dependent variable is monthly household expenditures on groceries (in $'s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables:     The correlation coefficient between the two variables in this regression is ___.

Accepted Answer

A)  0.682478 
B)  -0.83 
C)  0.83 
D)  -0.68 
E)  1.0008 
A)  0.682478 
B)  -0.83 
C)  0.83 
D)  -0.68 
E)  1.0008

Question 6

Abby Kratz, a market specialist at the market research firm of Saez, Sikes, and Spitz, is analyzing household budget data collected by her firm. Abby's dependent variable is monthly household expenditures on groceries (in $'s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables:     Abby's sample size (n) is ___.

Accepted Answer

A)  8 
B)  10 
C)  11 
D)  20 
E)  12 
A)  8 
B)  10 
C)  11 
D)  20 
E)  12

Question 7

A researcher has developed a regression model from fourteen pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two? tailed test and ɑ = 0.01. The critical table t value is ___.

Accepted Answer

A)  2.650 
B)  3.012 
C)  3.055 
D)  2.718 
E)  2.168 
A)  2.650 
B)  3.012 
C)  3.055 
D)  2.718 
E)  2.168

Question 8

Correlation is a measure of the degree of linear relationship between two variables.

Accepted Answer

A) True 
 B)False

Question 9

The numerical value of the coefficient of determination must be ___.

Accepted Answer

A)  between -1 and +1 
B)  between -1 and 0 
C)  between 0 and 1 
D)  equal to SSE/(n - 2) 
E)  between -100 and +100 
A)  between -1 and +1 
B)  between -1 and 0 
C)  between 0 and 1 
D)  equal to SSE/(n - 2) 
E)  between -100 and +100

Question 10

The following data represent the demand (Y) of an item at a local shop and their price (X).
   Use the data to determine the simple regression equation of price on demand if the correlation coefficient between x and y is -0.92.

Accepted Answer

The answer of The following data represent the demand (Y)...

Question 11

If a scatter plot of variables X and Y shows a trend that can be summarized to a large degree by a straight line with slope 0.8 and y-intercept 0.2 (i.e., Y = 0.2 + 0.8X), then the correlation coefficient between X and Y is ___.

Accepted Answer

A)  0.8, and there is a causal relation between X and Y (either X causes Y or Y causes X) 
B)  0.2, and there is a causal relation between X and Y (either X causes Y or Y causes X) 
C)  0.8, but there is no causal relation between X and Y 
D)  0.2, but there is no causal relation between X and Y 
E)  0.8, and there may be a causal relation between X and Y, but not necessarily 
A)  0.8, and there is a causal relation between X and Y (either X causes Y or Y causes X) 
B)  0.2, and there is a causal relation between X and Y (either X causes Y or Y causes X) 
C)  0.8, but there is no causal relation between X and Y 
D)  0.2, but there is no causal relation between X and Y 
E)  0.8, and there may be a causal relation between X and Y, but not necessarily

Question 12

One of the major uses of residual analysis is to test some of the assumptions underlying regression.

Accepted Answer

A) True 
 B)False

Question 13

A simple regression model developed for ten pairs of data resulted in a sum of squares of error, SSE = 125. The standard error of the estimate is ___.

Accepted Answer

A)  12.5 
B)  3.5 
C)  15.6 
D)  3.95 
E)  25 
A)  12.5 
B)  3.5 
C)  15.6 
D)  3.95 
E)  25

Question 14

The slope of the regression line, y = 21 − 5x, is 5.

Accepted Answer

A) True 
 B)False

Question 15

A quality manager is developing a regression model to predict the total number of defects as a function of the day of week the item is produced. Production runs are done 10 hours a day, 7 days a week. The explanatory variable is ___.

Accepted Answer

A)  day of week 
B)  production run 
C)  percentage of defects 
D)  number of defects 
E)  number of production runs 
A)  day of week 
B)  production run 
C)  percentage of defects 
D)  number of defects 
E)  number of production runs

Question 16

Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables:     Annie's sample size is ___.

Accepted Answer

A)  2 
B)  4 
C)  6 
D)  8 
E)  10 
A)  2 
B)  4 
C)  6 
D)  8 
E)  10

Question 17

The least squares regression equation for the distance X (in km) between an employee's place of residence and the time Y (in minutes) it takes to get to work is   
. If an employee lives 5km from work and takes 8 minutes to get there, what is the value of the residual?

Accepted Answer

The answer of The least squares regression equation for the...

Question 18

A researcher has developed the regression equation y = 2.164 + 1.3657x, where n = 6, the mean of x is 8.667, Sxx = 89.333, and Se = 3.44. The 90% confidence prediction interval for y when x = 1 is ___.

Accepted Answer

A)  (−2.14, 9.2) 
B)  (−2.54, 10.6) 
C)  (−3.04, 9.92) 
D)  (−3.14, 10.2) 
E)  (−3.24, 10.4) 
A)  (−2.14, 9.2) 
B)  (−2.54, 10.6) 
C)  (−3.04, 9.92) 
D)  (−3.14, 10.2) 
E)  (−3.24, 10.4)

Question 19

In regression analysis, R-squared is also called the ___.

Accepted Answer

A)  residual 
B)  coefficient of determination 
C)  coefficient of correlation 
D)  standard error of the estimate 
E)  sum of squares of regression 
A)  residual 
B)  coefficient of determination 
C)  coefficient of correlation 
D)  standard error of the estimate 
E)  sum of squares of regression

Question 20

A regression line minimizes the sum of the squared error values. This means that the regression line minimizes the sum of ___ from each point in the scatter point to the regression line.

Accepted Answer

A)  the squares of the distances 
B)  the squares of the horizontal distances (differences in the x-coordinates) 
C)  the squares of the vertical distances (differences in the x-coordinates) 
D)  the squares of the horizontal distances (differences in the y-coordinates) 
E)  the squares of the vertical distances (differences in the y-coordinates) 
A)  the squares of the distances 
B)  the squares of the horizontal distances (differences in the x-coordinates) 
C)  the squares of the vertical distances (differences in the x-coordinates) 
D)  the squares of the horizontal distances (differences in the y-coordinates) 
E)  the squares of the vertical distances (differences in the y-coordinates)

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed

The following data is to be used to construct a regression model: The regression equation is ___.

In the regression equation, y=2.164+1.3657x, n=6, the mean of x is 8.667, S_xx=89.333 and S_e=3.44. A 95% prediction interval for y when x = 8 is ___.

The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be ___.

A researcher has developed a regression model from fourteen pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two? tailed test and ɑ = 0.01. The critical table t value is ___.

Correlation is a measure of the degree of linear relationship between two variables.

The numerical value of the coefficient of determination must be ___.

The following data represent the demand (Y) of an item at a local shop and their price (X). Use the data to determine the simple regression equation of price on demand if the correlation coefficient between x and y is -0.92.

If a scatter plot of variables X and Y shows a trend that can be summarized to a large degree by a straight line with slope 0.8 and y-intercept 0.2 (i.e., Y = 0.2 + 0.8X), then the correlation coefficient between X and Y is ___.

One of the major uses of residual analysis is to test some of the assumptions underlying regression.

A simple regression model developed for ten pairs of data resulted in a sum of squares of error, SSE = 125. The standard error of the estimate is ___.

The slope of the regression line, y = 21 − 5x, is 5.

A quality manager is developing a regression model to predict the total number of defects as a function of the day of week the item is produced. Production runs are done 10 hours a day, 7 days a week. The explanatory variable is ___.

The least squares regression equation for the distance X (in km) between an employee's place of residence and the time Y (in minutes) it takes to get to work is . If an employee lives 5km from work and takes 8 minutes to get there, what is the value of the residual?

A researcher has developed the regression equation y = 2.164 + 1.3657x, where n = 6, the mean of x is 8.667, S_xx= 89.333, and S_e= 3.44. The 90% confidence prediction interval for y when x = 1 is ___.

In regression analysis, R-squared is also called the ___.

A regression line minimizes the sum of the squared error values. This means that the regression line minimizes the sum of ___ from each point in the scatter point to the regression line.

Introduction to Statistics

Organizing and Visualizing Data

Descriptive Statistics

Gathering Data

Probability

Decision Analysis and Expected Value

Discrete Probability Distributions

Continuous Distributions

Sampling Distributions

Confidence Intervals

Hypothesis Testing for Single Populations

Hypothesis Testing for Two Populations

Analysis of Variance Anova

Categorical Versus Categorical: Tests

Filters

Exam 14: Linear Correlation and Simple Linear Regression Analysis

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed

The following data is to be used to construct a regression model: The regression equation is ___.

In the regression equation, y=2.164+1.3657x, n=6, the mean of x is 8.667, Sxx=89.333 and Se=3.44. A 95% prediction interval for y when x = 8 is ___.

The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be ___.

A researcher has developed a regression model from fourteen pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two? tailed test and ɑ = 0.01. The critical table t value is ___.

Correlation is a measure of the degree of linear relationship between two variables.

The numerical value of the coefficient of determination must be ___.

The following data represent the demand (Y) of an item at a local shop and their price (X). Use the data to determine the simple regression equation of price on demand if the correlation coefficient between x and y is -0.92.

If a scatter plot of variables X and Y shows a trend that can be summarized to a large degree by a straight line with slope 0.8 and y-intercept 0.2 (i.e., Y = 0.2 + 0.8X), then the correlation coefficient between X and Y is ___.

One of the major uses of residual analysis is to test some of the assumptions underlying regression.

A simple regression model developed for ten pairs of data resulted in a sum of squares of error, SSE = 125. The standard error of the estimate is ___.

The slope of the regression line, y = 21 − 5x, is 5.

A quality manager is developing a regression model to predict the total number of defects as a function of the day of week the item is produced. Production runs are done 10 hours a day, 7 days a week. The explanatory variable is ___.

The least squares regression equation for the distance X (in km) between an employee's place of residence and the time Y (in minutes) it takes to get to work is . If an employee lives 5km from work and takes 8 minutes to get there, what is the value of the residual?

A researcher has developed the regression equation y = 2.164 + 1.3657x, where n = 6, the mean of x is 8.667, Sxx = 89.333, and Se = 3.44. The 90% confidence prediction interval for y when x = 1 is ___.

In regression analysis, R-squared is also called the ___.

A regression line minimizes the sum of the squared error values. This means that the regression line minimizes the sum of ___ from each point in the scatter point to the regression line.

Introduction to Statistics

Organizing and Visualizing Data

Descriptive Statistics

Gathering Data

Probability

Decision Analysis and Expected Value

Discrete Probability Distributions

Continuous Distributions

Sampling Distributions

Confidence Intervals

Hypothesis Testing for Single Populations

Hypothesis Testing for Two Populations

Analysis of Variance Anova

Categorical Versus Categorical: Tests

Filters

In the regression equation, y=2.164+1.3657x, n=6, the mean of x is 8.667, S_xx=89.333 and S_e=3.44. A 95% prediction interval for y when x = 8 is ___.

A researcher has developed the regression equation y = 2.164 + 1.3657x, where n = 6, the mean of x is 8.667, S_xx= 89.333, and S_e= 3.44. The 90% confidence prediction interval for y when x = 1 is ___.