Great Deal! Get Instant \$25 FREE in Account on First Order + 10% Cashback on Every Order Order Now

# 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...

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

## Solution

Mohd answered on Jan 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