Linear Regression

• For female cubs only.

• For male cubs only.

• For both male cubs and female cubs, with equal evidence.

• For both male cubs and female cubs, with more evidence for female cubs than for male cubs.

• For neither male cubs nor female cubs.

Ignoring the outlier, estimate the correlation of association shown in the scatterplot.

• r = 0.9

• r = 0.5

• r = 0.1

• r = -0.5

• r = -0.9

In a study of the relationship between SAT math scores (x) and SAT verbal scores (y), it was determined that the correlation coefficient was 0.68. Also, the mean SAT math score was 540 with a standard deviation of 125. The mean SAT verbal score was 498 with a standard deviation of 100. Which of the following is the least squares regression line for this data?

• y "hat" = 204.24 + 0.544x

• y "hat" = 66 + 0.8x

• y "hat" = –177 + 1.25x

• y "hat" = 39 + 0.85x

• There is not enough information to determine the equation

Suppose we fit a least-squares regression line to a set of bivariate data. If a residual plot shows a curved pattern, what must be true about the data?

• A LSRL is not a good model for the data.

• The correlation must be 0

• The coefficient of determination must be small.

• Outliers must be present.

• The standard deviation of the residuals must be large

• A

• B

• C

• D

• E

In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation was y-hat = 10 + 0.9x where y-hat is the predicted final-exam score and x is the score on the first test. Carla scored 95 on the first test. What is the predicted value of her score on the final exam?

• 85.5

• 90

• 95

• 95.5

• 98.5

In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation was y-hat= 10 + 0.9x where y-hat is the predicted final-exam score and x is the score on the first test. Bill scored a 90 on the first test and his residual was –2. What was his actual score on the final exam?

• 89

• 90

• 91

• 93

• Not enough information

A copy machine dealer has data on the number of copy machines x at each of 89 customer locations and the number of service calls in a month y at each location. Summary calculations give x̄ = 8.4, s_x = 2.1, ȳ = 14.2, s_y = 3.8, and r = 0.86. What is the slope of the least-squares regression line of number of service calls on number of copiers?

• 0.48

• 0.86

• 1.56

• 1.81

• 2.82

A copy machine dealer has data on the number of copy machines x at each of 89 customer locations and the number of service calls in a month y at each location. Summary calculations give x̄ = 8.4, s_x = 2.1, ȳ = 14.2, s_y = 3.8, and r = 0.86. What is the y-intercept of the least-squares regression line of number of service calls on number of copiers?

• 1.096

• 1.651

• 10.208

• 27.304

• -13.752

If the two variables in data set A have correlation r = 0.95 and the two variables in data set B have correlation

r = –0.95, which of the following is true?

• Data set A and data set B are both not linear.

• Data set A is more linear than data set B.

• Data set B is more linear than data set A.

• Data set A and data set B are equally linear.

• It cannot be determined which data set is more linear without additional information.