Include your SAS code and necessary output. (Do not need all output. Only provide output related to your answer for questions)

Use the data in Problem 7 in chapter 5. (Data “EX0507.txt” is listed below)

1) Use SAS to draw scatter plots between Y1 (Dist) and X, Y2 () and X.

2) Use SAS to determine the least-square estimates of the slope and intercept for each of the following straight-line regressions: Y1(Dist) on X (Y1 is response and X is predictor), and Y2 on X (Y2 is response and X is predictor). Write down the formula for the estimated regression lines. Draw (you can draw manually) the estimated lines on the appropriate scatter diagrams.

3) Which of the two variable pairs mentioned in part 1) seems to be better suited for straight-line regression?

MPH DIST SQRTDIST

25 37.4 6.12

35 57.7 7.6

60 337.6 18.37

45 142.5 11.94

50 182.4 13.51

37.5 67.5 8.22

30 37.5 6.12

55 225 15

60 258.1 16.07

65 297.4 17.25

50 170 13.04

20 20 4.47

15 13.5 3.67

27.5 40.8 6.39

55 207.8 14.42

40 105 10.25

45 132.6 11.52

17.5 19.1 4.37

22.5 25 5

Answered Same DayJan 27, 2022

Include your SAS code and necessary output. (Do not need all output. Only provide output related to your answer for questions)

Use the data in Problem 7 in chapter 5. (Data “EX0507.txt” is listed below)

1) Use SAS to draw scatter plots between Y1 (Dist) and X, Y2 () and X.

2) Use SAS to determine the least-square estimates of the slope and intercept for each of the following straight-line regressions: Y1(Dist) on X (Y1 is response and X is predictor), and Y2 on X (Y2 is response and X is predictor). Write down the formula for the estimated regression lines. Draw (you can draw manually) the estimated lines on the appropriate scatter diagrams.

Model: MODEL1

Equation:

y = c + mx

DIST = -122.34459 + 6.22708 * MPH

Dependent Variable: DIST

Analysis of Variance

Source

DF

Sum of

Squares

Mean

Square

F Value

Pr > F

Model

1

173474

173474

173.18

<.0001

E

o

17

17029

1001.69058

Co

ected Total

18

190503

Root MSE

31.64950

R-Square

0.9106

Dependent Mean

125.10000

Adj R-Sq

0.9054

Coeff...

Use the data in Problem 7 in chapter 5. (Data “EX0507.txt” is listed below)

1) Use SAS to draw scatter plots between Y1 (Dist) and X, Y2 () and X.

2) Use SAS to determine the least-square estimates of the slope and intercept for each of the following straight-line regressions: Y1(Dist) on X (Y1 is response and X is predictor), and Y2 on X (Y2 is response and X is predictor). Write down the formula for the estimated regression lines. Draw (you can draw manually) the estimated lines on the appropriate scatter diagrams.

Model: MODEL1

Equation:

y = c + mx

DIST = -122.34459 + 6.22708 * MPH

Dependent Variable: DIST

Analysis of Variance

Source

DF

Sum of

Squares

Mean

Square

F Value

Pr > F

Model

1

173474

173474

173.18

<.0001

E

o

17

17029

1001.69058

Co

ected Total

18

190503

Root MSE

31.64950

R-Square

0.9106

Dependent Mean

125.10000

Adj R-Sq

0.9054

Coeff...

SOLUTION.PDF## Answer To This Question Is Available To Download

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