1. the strength of the linear relationship

 

1.    The strength of the linear relationship between two numerical variables may be measured by the

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scatter diagram.

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coefficient of correlation.

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slope.

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Y-intercept.

10 points  

Question 2

1.      

If you wanted to analyze the correlation between the NUMBER OF HOURS PRACTICED and the NUMBER OF TARGETS HIT by a sharpshooter, which variable would be the dependent variable?

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Number of hours practiced

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Number of targets hit

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Neither one is dependent

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Either one could be dependent (impossible to determine)

10 points  

Question 3

1.      

Before proceeding with a simple linear regression, you should first construct a scatter diagram in order that you can remove all outliers from the data.
 

[removed]True

[removed]False

10 points  

Question 4

1.      

What does it mean to have a negative coefficient in the regression model?

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That variable reduces the coefficient of determination.

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The values for that variable are negative.

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There is an inverse relationship with that variable.

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The correlation is weak.

10 points  

Question 5

1.      

Assuming a linear relationship between X and Y, if the coefficient of correlation (r) equals -0.30,

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there is no correlation.

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the slope (b1) is negative.

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variable X is larger than variable Y.

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the variance of X is negative.

 

 

10 points  

Question 6

1.      

If the hypothesis test for correlation is found to be significant (i.e., we rejected the null hypothesis / accepted the alternate hypothesis), what can we automatically conclude about the strength of the correlation?

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We can conclude that the correlation must be strong.

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We can only conclude that the correlation is not weak

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We cannot conclude anything about the strength of the correlation yet.

10 points  

Question 7

1.      

A negative correlation coefficient implies that as the value of independent variable increases, the value of the dependent variable _________________.
 

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Increases

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Decreases

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Cannot be determined from the information given

10 points  

Question 8

1.      

There is a strong positive correlation between a baby’s weight and the size of his/her vocabulary. From this we can conclude that overeating will improve one’s vocabulary.
 

[removed]True

[removed]False

10 points  

Question 9

1.      

If the correlation coefficient (r) = 1.00, then

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all the data points must fall exactly on a straight line with a slope that equals 1.00.

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all the data points must fall exactly on a straight line with a negative slope.

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all the data points must fall exactly on a straight line with a positive slope.

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all the data points must fall exactly on a horizontal straight line with a zero slope.

10 points  

Question 10

1.      

Assume the regression model for predicting home prices by the square footage were: PRICE = 12510 + 83 (SQRFT) For every additional one square foot, how much does the price increase?

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$12,593

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$83

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$166

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Cannot be determined from the information given.

 

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