econometrics 120121Question 8The two regressions below are evaluating the Retail Price of bikes. The first regression (Summary Report below) was done using "type" and "weight" as independent variables and thesecond regression used "type", "weight", and an "interaction variable" (type times weight) as a third variable (2nd Summary Report below).122123EIRST BEGBESSION (Te Independent Yariables)SUMMARY OUTPUTRegression Statisties124125126Multiple R0.69127RSquare0.48128Adjusted R Square0.42Standard Error 385.99Observat12913019131132ANOVAAVSiicance F7.431332 2212853 110642716 2383841Regression0.01134135Residual148990136Total18 4596695137Coefficientandard En t StatPvaluetower 3pper ower 5Coper 5138I 771.94 1580.038Intercept1390.4890.632 ##### 4121.472 ##### 4121.472140ТуреWeight329.87 284.7281.1590.264 -273.721 933.470 -273.721 933.470141-13.1049.749-0.2630.796 -118.560 92.367 -118.560 92.367142SECOND BEGRESSION(Ihree independent Fariables)SUMMARY OUTPUT143144Regression StatisticsMultiple R 0.7512RSquare 0.5643Adjusted R Square 0.4771Standard Error 365.42145146147148149150Observations19151152ANOVAdfSignificance F864568 6.4746 0.0050153MSF3 2593705RegressionResidualTotal15415515 200298913353315618 4596695157Canticion Stonderdi tStet0.566158Intercept 847.37 1496.497ТуреWeightTypelweight -73.451590.580 ##### ##### ##### #####1601908.07972.5911.9620.069 -164.962 ##### -164.962 #####161-13.6647.099-0.2900.776 -114.045 86.734 -114.045 86.73416243.493-1.6890.112 -166.15419.251 -166.15419.251163There were 19 observations on which these regressions were based.Use the F statistic to test whether the addition of the "TyperWeight" variable is significant. What is the F statistic and the p-value for164165166that F statisitc?8. Ansver

Name: econometrics 120121Question 8The two regressions below are evaluating
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Description: econometrics 120121Question 8The two regressions below are evaluating the Retail Price of bikes. The first regression (Summary Report below) was done using "type" and "weight" as independent variables and thesecond regression used "type", "weight", a

The null and alternative hypotheses are H0: All the coefficients are equal to zero. H1: At least one…

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Residual Total 15 2002989 133533 18 4596695 Intercept 847.37 1496.497 1908.07 -13.66 0.566 1962 -0.290 -1689 0.580 0.069 -164.962 -164.962 Type Veight TypelVeight -73.45 972.591 47.099 43.493 0.776 -114.045 86.734 -114.045 86.734 0.112 -166.154 19.251 -166.154 19.251 There were 19 observations on which these regressions were based. Use the F statistic to test whether the addition of the "TypelVeight" variable is significant. Vhat is the F statistic and the p-value for that F statisito? 8. Ansver

Residual Total 15 2002989 133533 18 4596695 Intercept 847.37 1496.497 1908.07 -13.66 0.566 1962 -0.290 -1689 0.580 0.069 -164.962 -164.962 Type Veight TypelVeight -73.45 972.591 47.099 43.493 0.776 -114.045 86.734 -114.045 86.734 0.112 -166.154 19.251 -166.154 19.251 There were 19 observations on which these regressions were based. Use the F statistic to test whether the addition of the "TypelVeight" variable is significant. Vhat is the F statistic and the p-value for that F statisito? 8. Ansver

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Percentage

A percentage is a number indicated as a fraction of 100. It is a dimensionless number often expressed using the symbol %.

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Numbers are some measures used for counting. They can be compared one with another to know its position in the number line and determine which one is greater or lesser than the other.

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Question 8
The two regressions below are evaluating the Retail Price of bikes. The first regression (Summary Report below) was done using "type" and "weight" as independent variables and the
second regression used "type", "weight", and an "interaction variable" (type times weight) as a third variable (2nd Summary Report below).
122
123
EIRST BEGBESSION (Te Independent Yariables)
SUMMARY OUTPUT
Regression Statisties
124
125
126
Multiple R
0.69
127
RSquare
0.48
128
Adjusted R Square
0.42
Standard Error 385.99
Observat
129
130
19
131
132
ANOVA
AVS
iicance F
7.43
133
2 2212853 1106427
16 2383841
Regression
0.01
134
135
Residual
148990
136
Total
18 4596695
137
Coefficientandard En t Stat
Pvaluetower 3pper ower 5Coper 5
138
I 771.94 1580.038
Intercept
139
0.489
0.632 ##### 4121.472 ##### 4121.472
140
Туре
Weight
329.87 284.728
1.159
0.264 -273.721 933.470 -273.721 933.470
141
-13.10
49.749
-0.263
0.796 -118.560 92.367 -118.560 92.367
142
SECOND BEGRESSION(Ihree independent Fariables)
SUMMARY OUTPUT
143
144
Regression Statistics
Multiple R 0.7512
RSquare 0.5643
Adjusted R Square 0.4771
Standard Error 365.42
145
146
147
148
149
150
Observations
19
151
152
ANOVA
df
Significance F
864568 6.4746 0.0050
153
MS
F
3 2593705
Regression
Residual
Total
154
155
15 2002989
133533
156
18 4596695
157
Canticion Stonderdi tStet
0.566
158
Intercept 847.37 1496.497
Туре
Weight
Typelweight -73.45
159
0.580 ##### ##### ##### #####
160
1908.07
972.591
1.962
0.069 -164.962 ##### -164.962 #####
161
-13.66
47.099
-0.290
0.776 -114.045 86.734 -114.045 86.734
162
43.493
-1.689
0.112 -166.154
19.251 -166.154
19.251
163
There were 19 observations on which these regressions were based.
Use the F statistic to test whether the addition of the "TyperWeight" variable is significant. What is the F statistic and the p-value for
164
165
166
that F statisitc?
8. Ansver

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