Please interpret clearly and step by step.  Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions. Follow the decision map steps for interpretation, and then report the results in an academic style. Note that if any of the assumptions have been violated, you need to report it and continue as if it has not been violated.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Please interpret clearly and step by step. 

Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions. Follow the decision map steps for interpretation, and then report the results in an academic style. Note that if any of the assumptions have been violated, you need to report it and continue as if it has not been violated.

Regression Standardized Residual
1
Dimension Eigenvalue
1
4.809
2
161
3
017
4
.009
5
003
a Dependent variable: GallonsPerico
Frequency
50
10
Condition
Index
0
Collinearity Diagnostics
1.000
5.464
16.753
23.065
37,208
(Constan
.00
01
07
14
79
Number of
cylinders
00
01
30
57
13
Variance Proportions
Hores Power
of the Engine
.00
02
Regression Standardized Residual
Scatterplot
Dependent Variable: GallonsPer100Miles
34
01
63
Histogram
Dependent Variable: GallonsPer100Miles
Regression Standardized Predicted Value
Weight in 100
.00
00
05
43
51
Seconds to
reach to
speed 60
from D
Man-456E-15
Std Dev0.995
N-392
00
04
01
07
88
Transcribed Image Text:Regression Standardized Residual 1 Dimension Eigenvalue 1 4.809 2 161 3 017 4 .009 5 003 a Dependent variable: GallonsPerico Frequency 50 10 Condition Index 0 Collinearity Diagnostics 1.000 5.464 16.753 23.065 37,208 (Constan .00 01 07 14 79 Number of cylinders 00 01 30 57 13 Variance Proportions Hores Power of the Engine .00 02 Regression Standardized Residual Scatterplot Dependent Variable: GallonsPer100Miles 34 01 63 Histogram Dependent Variable: GallonsPer100Miles Regression Standardized Predicted Value Weight in 100 .00 00 05 43 51 Seconds to reach to speed 60 from D Man-456E-15 Std Dev0.995 N-392 00 04 01 07 88
Model
1
Variables Entered/Removed
Variables
Entered
Seconds to
reach to
speed 60
from 0,
Weight in 100
lb, Number of
cylinders,
Hores Power
of the Engineb
Model
1
Model
1
Variables
Removed
a. Dependent Variable: GallonsPer100Miles
b. All requested variables entered.
Sum of
Squares
893.674
195.014
1088.688
Method
Enter
(Constant)
Number of cylinders
Hores Power of the
Engine
ANOVA
df
4
387
391
-1.219
.141
1.844
Weight in 100 lb
Seconds to reach to
speed 60 from 0
a. Dependent Variable: GallonsPer100Miles
Std. Error of
the Estimate
.819
.70987
a. Predictors: (Constant), Seconds to reach to speed 60 from
0, Weight in 100 lb, Number of cylinders, Hores Power of
the Engine
b. Dependent Variable: GallonsPer100Miles
Model
1
Regression.
Residual
Total
a. Dependent Variable: GallonsPer100Miles
b. Predictors: (Constant), Seconds to reach to speed 60 from 0, Weight in 100 lb,
Number of cylinders, Hores Power of the Engine
.834
.053
Mean Square
Unstandardized Coefficients
B Std. Error
.410
.051
.269
Model Summary
R
.906ª
F
223.418 443.367
.504
.123
.021
R Square
.821
Standardized
Coefficients
Beta
.145
425
.425
.087
Adjusted R
Square
Sig.
.000b
Coefficients
t
-2.976
2.786
6.859
6.790
2.527
Sig.
.003
.006
.000
.000
.012
95.0% Confidence Interval for B
Lower Bound Upper Bound.
-2.025
-.414
.042
.241
1.315
2.372
.593
.012
1.076
.094
Correlations
Zero-order Partial
.840
.854
.886
-.456
.140
.329
.326
.127
Part
.060
.148
.146
.054
Collinearity Statistics
Tolerance VIF
.172
.120
118
.388
5.816
8.305
8.449
2.580
Transcribed Image Text:Model 1 Variables Entered/Removed Variables Entered Seconds to reach to speed 60 from 0, Weight in 100 lb, Number of cylinders, Hores Power of the Engineb Model 1 Model 1 Variables Removed a. Dependent Variable: GallonsPer100Miles b. All requested variables entered. Sum of Squares 893.674 195.014 1088.688 Method Enter (Constant) Number of cylinders Hores Power of the Engine ANOVA df 4 387 391 -1.219 .141 1.844 Weight in 100 lb Seconds to reach to speed 60 from 0 a. Dependent Variable: GallonsPer100Miles Std. Error of the Estimate .819 .70987 a. Predictors: (Constant), Seconds to reach to speed 60 from 0, Weight in 100 lb, Number of cylinders, Hores Power of the Engine b. Dependent Variable: GallonsPer100Miles Model 1 Regression. Residual Total a. Dependent Variable: GallonsPer100Miles b. Predictors: (Constant), Seconds to reach to speed 60 from 0, Weight in 100 lb, Number of cylinders, Hores Power of the Engine .834 .053 Mean Square Unstandardized Coefficients B Std. Error .410 .051 .269 Model Summary R .906ª F 223.418 443.367 .504 .123 .021 R Square .821 Standardized Coefficients Beta .145 425 .425 .087 Adjusted R Square Sig. .000b Coefficients t -2.976 2.786 6.859 6.790 2.527 Sig. .003 .006 .000 .000 .012 95.0% Confidence Interval for B Lower Bound Upper Bound. -2.025 -.414 .042 .241 1.315 2.372 .593 .012 1.076 .094 Correlations Zero-order Partial .840 .854 .886 -.456 .140 .329 .326 .127 Part .060 .148 .146 .054 Collinearity Statistics Tolerance VIF .172 .120 118 .388 5.816 8.305 8.449 2.580
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