The local government in Leeds is worried about the increasing amount of waste households in its city are producing. In order to gain a better understanding of what factors influence the amount of waste each household produces, consultants have gathered data from a random sample of 400 households on their average weekly waste, alongside information on the number of people living in the household, household income, whether anyone in the household works from home and whether the household has signed up to the ‘Make Leeds Greener’ initiative. The consultants have provided you with the following OLS output and asked you to provide a full discussion and interpretation of the statistical output.

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ISBN:9781119256830
Author:Amos Gilat
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The local government in Leeds is worried about the increasing amount of waste households in its city are producing. In order to gain a better understanding of what factors influence the amount of waste each household produces, consultants have gathered data from a random sample of 400 households on their average weekly waste, alongside information on the number of people living in the household, household income, whether anyone in the household works from home and whether the household has signed up to the ‘Make Leeds Greener’ initiative. The consultants have provided you with the following OLS output and asked you to provide a full discussion and interpretation of the statistical output.

 

Where the dependent variable:

Household average weekly waste (kgs) and the independent variables are:

Household size - number of people living in the household; Household Income - salary in £000’s;

Home work - someone working from home (1) ; no one working from home (0);

Concern for Environment - member of ‘Make Leeds Greener’ (1); not a member (0).

You are asked to answer the following questions:

i. Explain what the F-test is testing for in multiple regression models. Interpret the relevant evidence in the OLS output.

ii. Use the information above to calculate the R2 statistic. Explain your findings.

iii. Which of the explanatory variables are ‘statistically significant’ at the 1% level of significance and which are not? Explain the ‘test’ have you used to establish this and explain what it is testing for.

iv. Give a full written interpretation of each coefficient estimate.

v. What is multicollinearity and what are its consequences?

vi. If the tolerance/VIF value on the household income variable is 0.32/3.13, explain what this value means?

 

ANOVA
Model
Sum of Squares
Df
Mean Square
Sig.
1
Regression
1470500
367625
109.97
.000
Residual
1320500
395
3343.04
Total
2791000
399
Unstandardized Coefficients
Model
В
Std. Error
1
(Constant)
-0.098
0.054
Household size
0.308
0.084
Household income
0.105
0.039
Home work
1.034
0.689
Concern for
-0.875
0.321
Environment
Transcribed Image Text:ANOVA Model Sum of Squares Df Mean Square Sig. 1 Regression 1470500 367625 109.97 .000 Residual 1320500 395 3343.04 Total 2791000 399 Unstandardized Coefficients Model В Std. Error 1 (Constant) -0.098 0.054 Household size 0.308 0.084 Household income 0.105 0.039 Home work 1.034 0.689 Concern for -0.875 0.321 Environment
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