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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