1)

A national consumer magazine reported the following correlations. The correlation between car weight and car reliability is -0.70. The correlation between car weight and annual maintenance cost is 0.40. Which of the following statements are true?

I. Heavier cars tend to be less reliable.

II. Heavier cars tend to cost more to maintain.

III. Car weight is related more strongly to reliability than to maintenance cost.

• A.I only
• B.II only
• C.III only
• D.I and II only
• E.I, II, and III

2)

• There is an approximate linear relationship between the height of females and their age (from 5 to 18 years) described by: height = 50.3 + 6.01(age) where height is measured in cm and age in years. Which of the following is not correct?
• A.The estimated slope is 6.01, which implies that children increase by about 6 cm for each year they grow older.
• B.The estimated intercept is 50.3 cm which implies that children reach this height when they are 50.3/6.01=8.4 years old.
• C.The estimated height of a child who is 10 years old is about 110 cm.
• D.The average height of children when they are 5 years old is about 50% of the average height when they are 18 years old.
• E.My niece is about 8 years old and is about 115 cm tall. She is taller than average.

3)

• If the correlation coefficient (r) equals 0.61, it indicates that the proportion of the variation in the dependent variable explained by the variation in the independent variable is
• A.37%
• B.61%
• C.98%
• D.Cannot be determined

4)

• For children between the ages of 18 months and 29 months, there is approximately a linear relationship between "height" and "age". The relationship can be represented by: Y = 64.93 + 0.63(x), where Y represents height (in cm) and X represents age (in months). Joseph is 22.5 months old and is 80 cm tall. Is Joseph taller or shorter than his predicted height?
• A.Taller
• B.Shorter
• C.Cannot be determined

5)

You are given the following 95% CI for the slope coefficient for a linear regression of Y on X: (-10, -4). You can therefore conclude that the impact of the explanatory variable on the response variable is NOT statistically different from zero.

True

False

6)

• Larger values of R-Squared imply that the observations are more closely grouped about the
• A.average value of the independent variables
• B.average value of the dependent variable
• C.least squares line
• D.origin

7)

• In regression analysis, the variable that is used to explain the change in the outcome of an experiment, or process, is called
• A.the independent variable
• B.the predictor variable
• C.the explanatory variable
• D.all of the above (a-c) are correct
• E.none are correct

8)

Regression analysis was applied between $ sales (y) and $ advertising (x) across all the branches

of a major international corporation. The following regression function was obtained.

y = 5000 + 7.25x

If the advertising budgets of two branches of the corporation differ by $30,000, then what will be

the predicted difference in their sales?

• A.$217,500
• B.$222,500
• C.$5,000
• D.$7.25

9)

• The undergraduate admissions department hired a statistician to help them determine the strength of the relationship between ACT scores and cumulative college GPA. The statistician found the correlation coefficient between ACT score and cumulative GPA to be -0.98. What would you conclude?
• A.Students who have the best ACT scores tend to have the worst GPA's
• B.Students who have the best ACT scores tend to have the best GPA's
• C.None of the above

10)

• If there is a very strong correlation between two variables then the correlation coefficient must be
• A.greater than 1
• B.less than 0
• C.greater than 0
• D.need more information to determine