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Learn to test for heteroscedasticity in SPSS with data from the Canadian Fuel Consumption Report (2015).

This dataset example introduces testing for heteroscedasticity following a linear regression analysis, which rests on several assumptions: one is that the variance of the residuals from the model is constant and unrelated to the independent variable(s). Constant variance is homoscedasticity, while n...

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Bibliographic Details
Format: eBook
Language:English
Published: London : SAGE Publications, 2015.
Subjects:
Automobiles > Canada > Fuel consumption > Statistics.
Heteroscedasticity > Case studies.
Heteroscedasticity.
Research > Statistical methods > Case studies.
Research > Statistical methods.
Automobiles > Canada > Carburants > Consommation > Statistiques.
Recherche > Méthodes statistiques > Études de cas.
Recherche > Méthodes statistiques.
Automobiles > Fuel consumption.
Canada.
Case studies.
Statistics.
Online Access:Connect to the full text of the electronic book
Description
Summary:This dataset example introduces testing for heteroscedasticity following a linear regression analysis, which rests on several assumptions: one is that the variance of the residuals from the model is constant and unrelated to the independent variable(s). Constant variance is homoscedasticity, while non-constant variance is called heteroscedasticity. In this example, a simple regression model is estimated using a data subset from the 2015 Fuel Consumption Report from Natural Resources Canada to analyse whether the size of an automobile's engine predicts the highway fuel consumption of that automobile.
Physical Description:1 online resource : illustrations (black and white, and colour)
Audience:Specialized.
ISBN:9781473947955
1473947952