# 1. the strength of the linear relationship

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

 [removed] scatter diagram. [removed] coefficient of correlation. [removed] slope. [removed] Y-intercept.

10 points

Question 2

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?

 [removed] Number of hours practiced [removed] Number of targets hit [removed] Neither one is dependent [removed] 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?

 [removed] That variable reduces the coefficient of determination. [removed] The values for that variable are negative. [removed] There is an inverse relationship with that variable. [removed] 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,

 [removed] there is no correlation. [removed] the slope (b1) is negative. [removed] variable X is larger than variable Y. [removed] 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?

 [removed] We can conclude that the correlation must be strong. [removed] We can only conclude that the correlation is not weak [removed] 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 _________________.

 [removed] Increases [removed] Decreases [removed] 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

 [removed] all the data points must fall exactly on a straight line with a slope that equals 1.00. [removed] all the data points must fall exactly on a straight line with a negative slope. [removed] all the data points must fall exactly on a straight line with a positive slope. [removed] 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?

 [removed] \$12,593 [removed] \$83 [removed] \$166 [removed] Cannot be determined from the information given.

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