Deck 14: Introduction to Linear Regression and Correlation Analysis
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Deck 14: Introduction to Linear Regression and Correlation Analysis
1
Both a scatter plot and the correlation coefficient can distinguish between a curvilinear and a linear relationship.
False
2
If the correlation coefficient for two variables is computed to be a -0.70,the scatter plot will show the data to be downward sloping from left to right.
True
3
A bank is interested in determining whether its customers' checking balances are linearly related to their savings balances.A sample of n = 20 customers was selected and the correlation was calculated to be +0.40.If the bank is interested in testing to see whether there is a significant linear relationship between the two variables using a significance level of .05,the correct null and alternative hypotheses to test are:
H0 : r = 0.0
Ha : r ≠ 0.0
H0 : r = 0.0
Ha : r ≠ 0.0
False
4
A scatter plot is useful for identifying a linear relationship between the independent and dependent variable,but it is not particularly useful if the relationship is curvilinear.
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5
Two variables have a correlation coefficient that is very close to zero.This means that there is no relationship between the two variables.
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6
A study was recently conducted by Major League Baseball to determine whether there is a correlation between attendance at games and the record of home team's opponent.In this study,the dependent variable would be the record of the home team's opponent.
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7
A dependent variable is the variable that we wish to predict or explain in a regression model.
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8
A research study has stated that the taxes paid by individuals is correlated at a .78 value with the age of the individual.Given this,the scatter plot would show points that would fall on straight line on a slope equal to .78.
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9
When constructing a scatter plot,the dependent variable is placed on the vertical axis and the independent variable is placed on the horizontal axis.
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10
A bank is interested in determining whether its customers' checking balances are linearly related to their savings balances.A sample of n = 20 customers was selected and the correlation was calculated to be +0.40.If the bank is interested in testing to see whether there is a significant linear relationship between the two variables using a significance level of 0.05,the value of the test statistic is approximately t = 1.8516.
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11
A cellular phone service provider believes that there is negative correlation between the minutes used by its customers and the age of the customer.To test this,the following would be the appropriate null and alternative hypotheses:
H0 : ρ = 0.0
Ha : ρ ≠ 0.0
H0 : ρ = 0.0
Ha : ρ ≠ 0.0
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12
In developing a scatter plot,the decision maker has the option of connecting the points or not.
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13
The scatter plot is a two dimensional graph that is used to graphically represent the relationship between two variables.
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14
When a correlation is found between a pair of variables,this always means that there is a direct cause and effect relationship between the variables.
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15
A perfect correlation between two variables will always produce a correlation coefficient of +1.0
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16
The difference between a scatter plot and a scatter diagram is that the scatter plot has the independent variable on the x-axis while the independent variable is on the Y-axis in a scatter diagram.
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17
In conducting a hypothesis test for a correlation,the correct probability distribution to use is the F distribution.
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18
A correlation coefficient computed from a sample of data values selected from a population is called a statistic and is subject to sampling error.
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19
If two variables are related in a positive linear manner,the scatter plot will show points on the x,y space that are generally moving from the lower left to the upper right.
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20
A correlation of -0.9 indicates a weak linear relationship between the variables.
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21
In developing a simple linear regression model it is assumed that the distribution of error terms will be normally distributed for all levels of x.
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22
If two variables are uncorrelated,the sample correlation coefficient will be r = 0.00.
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23
State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
If the university wished to test the claim that the correlation between hours worked and GPA is negative,the following null and alternative hypotheses would be appropriate:
H0 : ρ < 0.0
Ha : ρ ≥ 0.0

H0 : ρ < 0.0
Ha : ρ ≥ 0.0
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24
In a simple regression model,the slope coefficient represents the average change in the independent variable for a one-unit change in the dependent variable.
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25
When the correlation coefficient for the two variables was -0.23,it implies that the two variables are not correlated because the correlation coefficient cannot be negative.
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26
The fact that teachers' salaries in Wisconsin are correlated with egg prices in Texas means that the two variables are spuriously correlated since a change in one variable could not cause the change in the other.
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27
State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
The test statistic for testing whether the two variables are significantly correlated is approximately z = 1.56.

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28
Given a sample of size n = 15 and a sample correlation of r = 0.7,the value of the test statistic for conducting a hypothesis test of the correlation is t = 3.53.
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29
Given a sample correlation r = -0.5 and a sample size of n = 30,the test statistic for testing whether the two variables are significantly correlated is approximately t = -3.055.
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30
You are given the following sample data for two variables:
Based upon these sample data,and testing at the 0.05 level of significance,the critical value for testing whether the population correlation coefficient is equal to zero is t = 2.2622.

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31
State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
In this study the independent variable is the number of hours worked off campus per week.

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32
If a set of data contains no values of x that are equal to zero,then the regression coefficient,b0,has no particular meaning.
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33
If the correlation between two variables is known to be statistically significant at the 0.05 level,then the regression slope coefficient will also be significant at the 0.05 level.
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34
If two variables are spuriously correlated,it means that the correlation coefficient between them is near zero.
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35
In conducting a hypothesis test on the correlation between a pair of variables,we assume that each variable is normally and independently distributed.
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36
If two variables are highly correlated,it not only means that they are linearly related,it also means that a change in one variable will cause a change in the other variable.
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37
State University recently randomly sampled ten students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
The correlation between these two variables is approximately -.461

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38
In a university statistics course a correlation of -0.8 was found between numbers of classes missed and course grade.This means that the fewer classes students missed,the higher the grade.
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39
You are given the following sample data for two variables:
The sample correlation coefficient for these data is approximately r = 0.755.

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40
When a pair of variables has a positive correlation,the slope in the regression equation will always be positive.
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41
Given a regression equation of
= 16 + 2.3x we would expect that an increase in x of 2.0 would lead to an average increase of y of 4.6.

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42
The standard error of the estimate for a simple linear regression model measures the variation in the slope coefficient from sample to sample.
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43
State University recently randomly sampled seven students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
A regression model with HOURS as the independent variable has an R-square equal to approximately .46.

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44
In a study of 30 customers' utility bills in which the monthly bill was the dependent variable and the number of square feet in the house is the independent variable,the resulting regression model is
= 23.40 + 0.4x.Based on this model,the expected utility bill for a customer with a home with 2,300 square feet is approximately $92.00.

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45
If it is known that a simple linear regression model explains 56 percent of the variation in the dependent variable and that the slope on the regression equation is negative,then we also know that the correlation between x and y is approximately -0.75.
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46
A study was recently done in which the following regression output was generated using Excel.
SUMMARY OUTPUT
Given this output,we would reject the null hypothesis that the population regression slope coefficient is equal to zero at the alpha = 0.05 level.
SUMMARY OUTPUT

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47
The following regression model has been computed based on a sample of twenty observations:
= 34.2 + 19.3x.The first observations in the sample for y and x were 300 and 18,respectively.Given this,the residual value for the first observation is approximately 81.6.

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48
The sum of the residuals in a least squares regression model will be zero only when the correlation between the x and y variables is statistically significant.
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49
If the correlation of x and y is -0.65,then coefficient of determination is -0.4225.
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50
In a study of 30 customers' utility bills in which the monthly bill was the dependent variable and the number of square feet in the house is the independent variable,the resulting regression model is
= 23.40 + 0.4x.Given this,the sample correlation coefficient is known to be positive.

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51
If the sample value of the intercept turns out to be an illogical value,this is acceptable as long as x = 0 is not within the range of the data.
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52
The sign on the intercept coefficient in a simple regression model will always be the same as the sign on the correlation coefficient.
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53
You are given the following sample data for two variables:
The regression model based on these sample data explains approximately 75 percent of the variation in the dependent variable.

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54
A study was recently done in which the following regression output was generated using Excel.
SUMMARY OUTPUT
Given this,we know that approximately 57 percent of the variation in the y variable is explained by the x variable.
SUMMARY OUTPUT

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55
Assume that we have found a regression equation of
= 3.6 - 2.4x,and that the coefficient of determination is 0.72,then the correlation of x and y must be about 0.849.

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56
In a study of 30 customers' utility bills in which the monthly bill was the dependent variable and the number of square feet in the house is the independent variable,the resulting regression model is
= 23.40 + 0.04x.Given this model,for a customer with a 2,000 square foot house and a monthly utility bill equal to $100.00,the residual from the regression model is approximately -$3.40.

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57
The following regression model has been computed based on a sample of twenty observations:
= 34.2 + 19.3x.Given this model,the predicted value for y when x = 40 is 806.2.

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58
If the correlation between the dependent variable and the independent variable is negative,the standard error of the regression slope coefficient in a simple linear regression model will also be negative.
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59
In a simple regression model,if the regression model is deemed to be statistically significant,it means that the regression slope coefficient is significantly greater than zero.
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60
Given a sample of data for use in simple linear regression,the values for the slope and the intercept are chosen to minimize the sum of squared errors.
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61
A manufacturing company is interested in predicting the number of defects that will be produced each hour on the assembly line.The managers believe that there is a relationship between the defect rate and the production rate per hour.The managers believe that they can use production rate to predict the number of defects.The following data were collected for 10 randomly selected hours.
Given these sample data,the simple linear regression model for predicting the number of defects is approximately
= 5.67 + 0.048x.


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62
When the intercept in a regression equation is deemed not significantly different from 0,then in making predictions for y,0.0 should be used as the value of the intercept rather than the estimated intercept value.
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63
In analyzing the relationship between two variables,a scatter plot can be used to detect which of the following?
A)A positive linear relationship
B)A curvilinear relationship
C)A negative linear relationship
D)All of the above
A)A positive linear relationship
B)A curvilinear relationship
C)A negative linear relationship
D)All of the above
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64
If the R-squared value for a regression model is high,the regression model will necessarily provide accurate forecasts of the y variable.
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65
A study was recently performed by the Internal Revenue Service to determine how much tip income waiters and waitresses should make based on the size of the bill at each table.A random sample of bills and resulting tips were collected and the following regression results were observed:
SUMMARY OUTPUT
Given this output,the upper limit for the 95 percent confidence interval estimate for the true regression slope coefficient is approximately 0.28.
SUMMARY OUTPUT

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66
State University recently randomly sampled seven students and analyzed grade point average (GPA)and number of hours worked off-campus per week.The following data were observed:
In testing the significance of the regression slope coefficient for the independent variable,HOURS,the calculated test statistic is approximately t = -1.47.

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67
If a simple least squares regression model is developed based on a sample where the two variables are known to be positively correlated,the sign on the regression coefficient will be positive also.
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68
When regression analysis is used for descriptive purposes,two of the main items of interest are whether the sign on the regression slope coefficient is positive or negative and whether the regression slope coefficient is significantly different from zero.
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69
In a simple linear regression analysis,if the test statistic for testing the significance of the regression slope coefficient is 3.6,the F ratio from the analysis of variance table is known to be 12.96
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70
A study was recently performed by the Internal Revenue Service to determine how much tip income waiters and waitresses should make based on the size of the bill at each table.A random sample of bills and resulting tips were collected and the following regression results were observed:
SUMMARY OUTPUT
Given this output,the point estimate for the average tip per dollar amount of the bill is approximately $0.21.
SUMMARY OUTPUT

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71
The values of the regression coefficients are found such the sum of the residuals is minimized.
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72
If a simple least squares regression model is developed based on a sample where the two variables are known to be positively correlated,the sum of the residuals will be positive.
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73
The prediction interval developed from a simple linear regression model will be at its narrowest point when the value of x used to predict y is equal to the mean value of x.
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74
When calculating prediction intervals for predicted values of y based on a given x,all 95 percent prediction intervals will be of equal width.
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75
A high coefficient of determination (R2)implies that the regression model will be a good predictor for future values of the dependent variable given the value of the independent variable.
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76
If the R-square value for a simple linear regression model is .80,the correlation between the two variables is known to be .64.
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77
A positive population slope of 12 (β1 = 12)means that a 1-unit increase in x causes an average 12-unit increase in y.
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78
Given the following regression equation,the predicted value for y when x = 0.5 is about 4.57 

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79
In simple linear regression,the t-test for the slope and the F-test are both conducting the same hypothesis test.
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80
A regression model that is deemed to have a regression slope coefficient that could be equal to zero should not be used for prediction since there is no established linear relationship between the x and y variable.
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