Deck 15: Simple Linear Regression and Correlation
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Deck 15: Simple Linear Regression and Correlation
1
True or False The value of the variation explained by the regression line can never be larger than 1.0.
False
2
True or False The simple linear regression model assumes that regardless of the value for x,the standard deviation of the distribution of y values about the regression line is the same.
True
3
True or False In a simple linear regression model,the residual is the horizontal distance from the regression line to an observed data point.
False
4
True or False The coefficient of determination is a number that indicates both the direction and the strength of the linear relationship between the dependent and independent variable.
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5
True or False For a given data set of (x,y)values,an infinite number of possible regression equations can be fitted to the corresponding scatter diagram,and each equation will have a unique combination of values for the y-intercept b0 and the slope b1.However,only one equation will be the "best fit" as defined by the least-squares criterion.
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6
Another name for the residual term in a regression equation is:
A) random error.
B) heteroscedasticity.
C) homoscedasticity.
D) pooled variances.
E) residual analysis.
A) random error.
B) heteroscedasticity.
C) homoscedasticity.
D) pooled variances.
E) residual analysis.
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7
A regression analysis between weight (y in pounds)and height (x in inches)resulted in the following least squares line: = 120 + 5x.This implies that if the height is increased by 1 inch,the weight is expected to:
A) increase by 1 pound.
B) decrease by 1 pound.
C) increase by 5 pounds.
D) decrease by 24 pounds.
A) increase by 1 pound.
B) decrease by 1 pound.
C) increase by 5 pounds.
D) decrease by 24 pounds.
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8
Simple linear regression requires that the scales of measurement be expressed in either:
A) nominal or ordinal.
B) ordinal or ratio.
C) interval or ratio.
D) nominal or ratio.
E) nominal or interval.
A) nominal or ordinal.
B) ordinal or ratio.
C) interval or ratio.
D) nominal or ratio.
E) nominal or interval.
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9
True or False The simple linear regression model assumes that the y values are statistically independent of each other but the residuals are statistically dependent of each other.
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10
True or False The least-squares criterion requires that the sum of the squared deviations between the y values in the scatter diagram and the y values predicted by the equation be minimized.
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11
In the sample regression line the term b0 is the y-intercept; this is the value of y where the line intersects the y-axis whenever x = 0.
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12
True or False When the predicted values of y and the actual values of y are the same,the standard error of estimate will be 0.0.
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13
True or False The simple linear regression model assumes that for any given value of x,the population of residuals will be normally distributed with a mean of zero and a standard deviation of 1.
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14
True or False An ANOVA test based on SST and SSR is equivalent to t-test for the coefficient of correlation and the slope.
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15
A regression analysis between sales (in $1000)and advertising (in $100)resulted in the following least squares line: = 75 +6x.This implies that if advertising is $800,then the predicted amount of sales (in dollars)is:
A) $4875.
B) $123,000.
C) $487,500.
D) $12,300.
A) $4875.
B) $123,000.
C) $487,500.
D) $12,300.
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16
Which of the following statements is true regarding the simple linear regression model
A) is a value of the dependent variable (y) and xi is a value of the independent variable (x).
B) 0 is the y-intercept of the regression line.
C) 1 is the slope of the regression line.
D) 1 is a random error,or residual.
E) All of the above are true statements.
A) is a value of the dependent variable (y) and xi is a value of the independent variable (x).
B) 0 is the y-intercept of the regression line.
C) 1 is the slope of the regression line.
D) 1 is a random error,or residual.
E) All of the above are true statements.
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17
Regardless of the value of x,the standard deviation of the distribution of y values about the regression line is the same.This assumption of equal standard deviations about the regression line is called:
A) random error.
B) heteroscedasticity.
C) homoscedasticity.
D) pooled variances.
E) residual analysis.
A) random error.
B) heteroscedasticity.
C) homoscedasticity.
D) pooled variances.
E) residual analysis.
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18
A regression analysis between sales (in $1000)and advertising (in $)resulted in the following least squares line: = 80,000 + 5x.This implies that an:
A) increase of $1 in advertising is expected to result in an increase of $5 in sales.
B) increase $5 in advertising is expected to result in an increase of $5,000 in sales.
C) increase of $1 in advertising is expected to result in an increase of $80,005 in sales.
D) increase of $1 in advertising is expected to result in an increase of $5,000 in sales.
A) increase of $1 in advertising is expected to result in an increase of $5 in sales.
B) increase $5 in advertising is expected to result in an increase of $5,000 in sales.
C) increase of $1 in advertising is expected to result in an increase of $80,005 in sales.
D) increase of $1 in advertising is expected to result in an increase of $5,000 in sales.
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19
The residual is defined as the difference between the:
A) actual value of y and the estimated value of y.
B) actual value of x and the estimated value of x
C) actual value of y and the estimated value of x.
D) actual value of x and the estimated value of y.
A) actual value of y and the estimated value of y.
B) actual value of x and the estimated value of x
C) actual value of y and the estimated value of x.
D) actual value of x and the estimated value of y.
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20
True or False The coefficient of determination can be described in terms of the total variation in y versus the unexplained variation in y.
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21
If the standard error of estimate = 18 and n = 10, then the error sum of squares, SSE, is:
A) 2916.
B) 2592.
C) 1800.
D) 3240.
A) 2916.
B) 2592.
C) 1800.
D) 3240.
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22
The following values are listed as coefficients of correlation (r).The one that indicates an inverse relationship between the two variables x and y is:
A) 0.0.
B) -0.8.
C) 0.9.
D) 1.3.
E) -1.4.
A) 0.0.
B) -0.8.
C) 0.9.
D) 1.3.
E) -1.4.
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23
For a given value of x,the estimation interval for an individual y observation is called the:
A) confidence interval.
B) residual.
C) prediction interval.
D) least-squares interval.
E) standard error of estimate.
A) confidence interval.
B) residual.
C) prediction interval.
D) least-squares interval.
E) standard error of estimate.
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24
Correlation analysis requires that the scales of measurement be expressed in either:
A) nominal or ordinal.
B) ordinal or ratio.
C) interval or ratio.
D) nominal or ratio.
E) nominal or interval.
A) nominal or ordinal.
B) ordinal or ratio.
C) interval or ratio.
D) nominal or ratio.
E) nominal or interval.
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25
In simple linear regression,the coefficient of correlation r and the least squares estimate of the population slope :
A) must have the same numerical value.
B) must have opposite signs.
C) must have the same sign.
D) may have opposite signs or the same sign.
A) must have the same numerical value.
B) must have opposite signs.
C) must have the same sign.
D) may have opposite signs or the same sign.
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26
Which of the following table values would be appropriate for a 95% confidence interval for the mean of y from a simple linear regression problem if the sample size is 7?
A) 1.895
B) 2.015
C) 2.365
D) 2.571
E) 1.960
A) 1.895
B) 2.015
C) 2.365
D) 2.571
E) 1.960
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27
Given the least squares regression line = -2.88 + 1.77x,and a coefficient of determination of 0.81,the coefficient of correlation is:
A) -0.88.
B) +0.88.
C) +0.90.
D) -0.90.
A) -0.88.
B) +0.88.
C) +0.90.
D) -0.90.
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28
The regression line = 3 + 2x has been fitted to the data points (4,8), (2,5), and (1,2). The residual sum of squares will be:
A) 10.
B) 15.
C) 13.
D) 22.
A) 10.
B) 15.
C) 13.
D) 22.
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29
The number of degrees of freedom associated with the standard error of estimate is
A) n-1 since only the slope is estimated from sample data.
B) n-1 since only the intercept is estimated from sample data.
C) n-1 since only the predicted value of y is estimated from sample data.
D) n-2 since the slope and the intercept are estimated from sample data.
A) n-1 since only the slope is estimated from sample data.
B) n-1 since only the intercept is estimated from sample data.
C) n-1 since only the predicted value of y is estimated from sample data.
D) n-2 since the slope and the intercept are estimated from sample data.
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30
For the values of the coefficient of determination listed below,which one implies the greatest value of SSR (regression sum of squares)given that SST = 500?
A) 0.95
B) -1.00
C) 0.28
D) 0.00
E) -0.88
A) 0.95
B) -1.00
C) 0.28
D) 0.00
E) -0.88
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31
In order to estimate with 95% confidence the expected value of y in a simple linear regression problem,a random sample of 10 observations is taken.Which of the following t-table values listed below would be used?
A) 2.228
B) 2.306
C) 1.860
D) 1.812
A) 2.228
B) 2.306
C) 1.860
D) 1.812
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32
In a regression problem the following pairs of (x,y)are given: (2,1),(2,-1),(2,0),(2,-2)and (2,2).That indicates that the:
A) coefficient of correlation is -1.
B) coefficient of correlation is 0.
C) coefficient of correlation is 1.
D) coefficient of determination is between -1 and 1.
A) coefficient of correlation is -1.
B) coefficient of correlation is 0.
C) coefficient of correlation is 1.
D) coefficient of determination is between -1 and 1.
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33
In publishing the results of some research work,the following values of the coefficient of determination were listed.Which one would appear to be incorrect?
A) 0.91
B) 0.06
C) 0.47
D) -0.64
E) 0.00
A) 0.91
B) 0.06
C) 0.47
D) -0.64
E) 0.00
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34
All of the values of an independent variable equal the same number.Regressing a dependent variable on this independent variable will result in a coefficient of determination (r 2 )of:
A) 0.0.
B) -1.0.
C) 2.3.
D) -2.3.
E) 1.0.
A) 0.0.
B) -1.0.
C) 2.3.
D) -2.3.
E) 1.0.
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35
The vertical spread of the data points about the regression line is measured by the:
A) regression coefficient.
B) standard error of estimate.
C) y-intercept.
D) homoscedasticity coefficient.
E) t-ratio.
A) regression coefficient.
B) standard error of estimate.
C) y-intercept.
D) homoscedasticity coefficient.
E) t-ratio.
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36
An indication of no linear relationship between two variables would be:
A) a coefficient of determination equal to 1.
B) a coefficient of determination equal to -1.
C) a coefficient of correlation of 0.
D) a coefficient of correlation equal to -1.
E) Both "A" and "B" are correct.
A) a coefficient of determination equal to 1.
B) a coefficient of determination equal to -1.
C) a coefficient of correlation of 0.
D) a coefficient of correlation equal to -1.
E) Both "A" and "B" are correct.
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37
The value for SSE equals zero.This means that the coefficient of determination (r 2 )must equal:
A) 0.0.
B) -1.0.
C) 2.3.
D) -2.3.
E) 1.0.
A) 0.0.
B) -1.0.
C) 2.3.
D) -2.3.
E) 1.0.
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38
If all the points in a scatter diagram lie on the least squares regression line,then the coefficient of correlation:
A) must be 1.0.
B) must be -1.0.
C) must be either 1.0 or -1.0.
D) must be 0.
A) must be 1.0.
B) must be -1.0.
C) must be either 1.0 or -1.0.
D) must be 0.
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39
Correlation analysis is used to determine the:
A) strength of the relationship between x and y.
B) least squares estimates of the regression parameters.
C) predicted value of y for a given value of x.
D) coefficient of determination.
A) strength of the relationship between x and y.
B) least squares estimates of the regression parameters.
C) predicted value of y for a given value of x.
D) coefficient of determination.
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40
In a regression problem,if the coefficient of determination is 0.90,this means that:
A) 90% of the y values are positive.
B) 90% of the variation in y can be explained by the regression line
C) 90% of the x values are equal.
D) 90% of the variation in x can be explained by regression line.
A) 90% of the y values are positive.
B) 90% of the variation in y can be explained by the regression line
C) 90% of the x values are equal.
D) 90% of the variation in x can be explained by regression line.
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41
____________________ provides a "best-fit" mathematical equation for the values of two variables,x and y.
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42
Briefly describe each of the following:
a)Homoscedasticity
b)Residual
a)Homoscedasticity
b)Residual
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43
Briefly describe each of the following:
A)An inverse relationship between variables __________________________________
B)A direct relationship between variables __________________________________
C)A linear relationship between variables __________________________________
D)A curvilinear relationship between variables __________________________________
A)An inverse relationship between variables __________________________________
B)A direct relationship between variables __________________________________
C)A linear relationship between variables __________________________________
D)A curvilinear relationship between variables __________________________________
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44
______________________________ measures the strength of the relationship between the dependent and independent variables.
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45
If the coefficient of correlation is either ____________________ or ____________________,then the regression line will actually include all of the data points and the line will be a perfect fit.
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46
The coefficient of determination can take on values between ____________________ and ____________________,inclusive.
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47
If the sum of squares due to regression (SSR)is 60,which of the following must be true?
A) The coefficient of correlation is 0.9.
B) The total sum of squares (SST)is at least 60.
C) The y-intercept is positive.
D) The slope,b,is positive.
E) The coefficient of determination is 0.81.
A) The coefficient of correlation is 0.9.
B) The total sum of squares (SST)is at least 60.
C) The y-intercept is positive.
D) The slope,b,is positive.
E) The coefficient of determination is 0.81.
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48
Correlation analysis provides us with two important measures of the strength: (1)the coefficient of ____________________ and (2)the coefficient of ____________________.
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49
The ____________________ requires that the sum of the squared deviations between y values in the scatter diagram and y values predicted by the equation be minimized.
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50
The symbol for the independent variable is ____________________ and the symbol for the dependent variable is ____________________.
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51
The coefficient of correlation assumes values between ____________________ and ____________________,inclusive.
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52
The assumption of equal standard deviations about the regression line is called _________________________.
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53
A simple linear regression problem produced the following sum of squares:
= 240,
= 60,
= 180
What percentage of the variation in y is explained by the regression line?



What percentage of the variation in y is explained by the regression line?
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54
If the coefficient of correlation is -0.90,what percentage of the variation in y is explained by the regression line?
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55
Consider the following data values of variables x and y
Use Excel or Minitab to construct a scatter diagram of the data points

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56
If the total variation in y values is 200,and the variation explained by regression line is 180,then the coefficient of determination is equal to ____________________.
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57
In a simple linear model,testing whether the slope of the population regression line is zero is the same as testing whether or not the population ____________________ equals zero.
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58
One way to examine whether two variables might be linearly related is to construct a ______________________________.
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59
If the coefficient of correlation r is positive,then the dependent variable and the independent variable x are said to be ____________________ related.However,if r is negative,then x and y are said to be ____________________ related.
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60
The variation explained by regression line is denoted by ____________________,while the variation not explained by regression line is denoted by ____________________.
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61
NARRBEGIN: Used cars
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Using the least-squares regression line,predict the selling price of a car with 55,000 miles.
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Using the least-squares regression line,predict the selling price of a car with 55,000 miles.
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62
NARRBEGIN: Used cars
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Identify the dependent and independent variable.
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Identify the dependent and independent variable.
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63
NARRBEGIN: Used cars
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Find the least-squares regression line.
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Find the least-squares regression line.
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64
NARRBEGIN: Teacher
A statistics teacher collected the following data to determine if the number of hours a student studied during the semester could be used to predict the final grade for the course.

In testing the hypotheses
vs.
,what is the value of the test statistic?
A statistics teacher collected the following data to determine if the number of hours a student studied during the semester could be used to predict the final grade for the course.

In testing the hypotheses


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65
NARRBEGIN: Teacher
A statistics teacher collected the following data to determine if the number of hours a student studied during the semester could be used to predict the final grade for the course.

In testing the hypotheses
vs.
,what is the conclusion at the 0.05 significance level?
A statistics teacher collected the following data to determine if the number of hours a student studied during the semester could be used to predict the final grade for the course.

In testing the hypotheses


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66
NARRBEGIN: GPA
The following table shows the grade point average (GPA)for 5 students along with their entrance exam scores for MBA programs (GMAT).Develop a model that would predict the GPA of a student based on their GMAT score.

Determine the standard error of estimate.
The following table shows the grade point average (GPA)for 5 students along with their entrance exam scores for MBA programs (GMAT).Develop a model that would predict the GPA of a student based on their GMAT score.

Determine the standard error of estimate.
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67
NARRBEGIN: Number of years
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

Identify the dependent and independent variables.
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

Identify the dependent and independent variables.
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68
NARRBEGIN: GPA
The following table shows the grade point average (GPA)for 5 students along with their entrance exam scores for MBA programs (GMAT).Develop a model that would predict the GPA of a student based on their GMAT score.

Determine the least-squares regression line.
The following table shows the grade point average (GPA)for 5 students along with their entrance exam scores for MBA programs (GMAT).Develop a model that would predict the GPA of a student based on their GMAT score.

Determine the least-squares regression line.
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69
NARRBEGIN: Teacher
A statistics teacher collected the following data to determine if the number of hours a student studied during the semester could be used to predict the final grade for the course.

In testing the hypotheses
vs.
,what is the rejection region at the 0.05 significance level?
A statistics teacher collected the following data to determine if the number of hours a student studied during the semester could be used to predict the final grade for the course.

In testing the hypotheses


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70
NARRBEGIN: X and Y
Consider the following data values of variables x and y

Given that when a simple linear regression model applied to the data,it produced the following residuals:
0.062,-0.195,0.548,-0.682,0.089,-0.168,and 0.346.
Apply the Lilliefors test to the residuals at
= 0.05.What is your conclusion?
Consider the following data values of variables x and y

Given that when a simple linear regression model applied to the data,it produced the following residuals:
0.062,-0.195,0.548,-0.682,0.089,-0.168,and 0.346.
Apply the Lilliefors test to the residuals at

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71
NARRBEGIN: X and Y
Consider the following data values of variables x and y

Given that the simple linear regression equation is
,use Minitab to create a normal probability plot of the residuals.
Consider the following data values of variables x and y

Given that the simple linear regression equation is

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72
NARRBEGIN: Used cars
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Consider the following data values of variables x and y
What does the scatter diagram tell you about the relationship between x and y?
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Consider the following data values of variables x and y


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73
What does the following scatter diagram tell you about the relationship between x and y? 

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74
Construct a 95% prediction interval for an individual y value when x = 6.5.
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75
NARRBEGIN: Number of years
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

Find the least-squares regression line.
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

Find the least-squares regression line.
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76
NARRBEGIN: Used cars
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Consider the following data values of variables x and y
Use Minitab or Excel to construct a scatter diagram of the data points and plot the least squares regression line on it.
The following table shows the selling prices and mileages for 7 used cars of a certain model.

Consider the following data values of variables x and y

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77
NARRBEGIN: Number of years
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

The divisor of the standard error of estimate in simple linear regression is:
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

The divisor of the standard error of estimate in simple linear regression is:
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78
NARRBEGIN: Number of years
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

Using the least-squares regression line,predict the salary of an employee with 11 years of experience.
Data was collected to describe the relationship between salary and number of years of working experience at a particular organization and is shown below in the following table.

Using the least-squares regression line,predict the salary of an employee with 11 years of experience.
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79
Construct a 95% confidence interval for the mean GPA when GMAT = 6.5.
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80
A simple linear regression problem produced the following sum of squares:
= 240,
= 60,
= 180
What percentage of the variation in y is not explained by the regression line?



What percentage of the variation in y is not explained by the regression line?
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