Linear Regression and Correlation Practice

Estimate the correlation coefficient for this scatterplot.

• r = 1.2

• r = 0.89

• r = 0

• r = -0.89

what is the formula for linear regression?

• y=mx+b

• a^2+b^2=c^2

• y1~mx1+b

• (1/2)(b)(h)

What letter do we use to represent correlation coefficient?

• c

• r

• p

• h

The scatter plot below shows the number of books read by students in Mrs. Hall’s English class and their final grades. Which statement represents the best description about the line of best fit?

• The more books students read, the lower their English grade.

• The more books students read, the higher their English grade.

• The fewer books students read, the higher their English grade.

• No relationship exists between the number of books students read and their English grades.

Data is analyzed comparing hours studied and grades. It is determined that the correlation coefficient is 0.92. What does this mean?

• There is a strong positive correlation between studying and grades.

• There is a strong negative correlation between studying and grades.

• There is a weak positive correlation between studying and grades.

• There is a weak negative correlation between studying and grades.

• m is 2.95

• Mr. Fisher has to spend $4.95

• For every 1 roomate who wants ice cream, the cost goes up $2.95.

• For every 1 roommate who wants ice cream, the cost goes up $4.95

• If no roommates want ice cream, Mr. Fisher is going to spend $4.95 on himself.

• If no roommates want ice cream, Mr. Fisher is going to spend $2.95

• For every 1 roomate who wants ice cream, the cost goes up $2.95.

• For every 1 roommate who wants ice cream, the cost goes up $4.95

Estimate the correlation coefficient for this scatterplot.

• r = -0.9

• r = 1

• r = 0.9

• r = -1

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  ŷ = 10 + 0.9x where y is the 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

• none of these

A set of data describes the relationship between the size of annual salary raises and the performance ratings for employees of a certain company. The least squares regression equation is ŷ = 1400 + 2000x where y is the raise amount (in dollars) and x is the performance rating. Which of the following statements must be true?

• For each one-point increase in performance rating, the raise will increase on average by$2000.

• The actual relationship between salary raises and performance rating is linear.

• The residuals for half the observations in the dataset will be positive.

• The correlation between salary raise and performance rating is negative.

• For each one-point increase in performance rating, the raise will increase on average by$1400.