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
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
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
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
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
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
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
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
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. |
11 years ago
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