### Question details

Homework week 2 Result 100%
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 Homework week 2

1. Two variables have a positive linear correlation. Does the dependent variable increase or decrease as the independent variable increases?

The  dependent  variable  increases.

O     The dependent variable decreases.

1. Discuss the difference between r and p. Choose the correct answers below.

r represents the   sample correlation  coefficient.

p represents the   population correlation  coefficient.

1. The scatter plot of a paired data set is shown. Determine whether there is a perfect positive linear correlation, a strong positive linear correlation, a perfect negative linear correlation, a strong negative linear correlation, or no linear correlation between the variables.

O   strong positive linear correlation O   strong negative linear correlation O  perfect positive linear correlation O   perfect negative linear correlation     no linear correlation

1. Identify the explanatory variable and the response  variable.

A farmer wants to determine if the type of fertilizer used by similar crops can be used to predict the harvest of the crop.

The explanatory variable is the type of fertilizer The response variable is the   harvest of the crop  .

A.

B.

C.

D.

A.

B.

C.

A.

B.

C.

D.

A.

B.

C.

D.

A.

B.

C.

D.

E.

F.

A.                                                                                                   B.

C.                                                                                                   D.

A.                                                                                                   B.

C.                                                                                                       D.

1. Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation?

1. Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation?

A

1. The equation used to predict college GPA (range 0-4.0) is y = 0.16 + 0.52x 1 + 0.002x 2 , where x 1 is  high

school GPA (range 0-4.0) and x2 is college board score (range 200-800). Use the multiple regression equation to predict college GPA for a high school GPA of 3.6 and a college board  score of   400.

1. The equation used to predict the total body weight (in pounds) of a female athlete at a certain    school is

A

y = - 120 + 3.82x 1 + l.09x2 , where x 1 is the female athlete's height

(in inches) and x2 is the female athlete's percent body fat. Use the multiple regression equation to predict the total body weight for a female athlete who is 62 inches tall and has 27% body    fat.

The predicted total body weight for a female athlete who is 62 inches tall and has 27% body fat is 146.3 pounds.

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