By Day 3, Estimate a multiple regression model that answers your research questi
ID: 2909580 • Letter: B
Question
By Day 3, Estimate a multiple regression model that answers your research question. Post your response to the following:
What is your research question?
Interpret the coefficients for the model, specifically commenting on the dummy variable.
Does the model meet all of the assumptions?
Be sure and comment on what assumptions were not met and the possible implications.
Is there any possible remedy for one the assumption violations?
Model Summa Adjusted R Square Std. Error of Durbin- Watson R Square the Estimate 9226 a. Predictors: (Constant), SouthernAfrica, EastAfrica, WestAfrica Model 048 048 1.285 b. Dependent Variable: Lived Poverty Index (average index of 5 poverty items) ANOVAa Sum of Squares Model df Mean Square Sig Regression Residual Total 2193.473 43338.320 5531.793 731.158 859.051 50919 851 50922 a. Dependent Variable: Lived Poverty Index (average index of 5 poverty items) b. Predictors: (Constant), SouthernAfrica, EastAfrica, WestAfrica Coefficients Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Tolerance Model Std. Error Beta Sig VIF (Constant) WestAfrica EastAfrica SouthernAfrica 012 63.113 47.296 24740.247 29.365 758 378 495 383 2.644 632 407 016 2.019 205 a. Dependent Variable: Lived Poverty Index (average index of 5 poverty items)Explanation / Answer
The research question is: whether lived poverty index depends on Southern Africa, East Africa, West Africa. Here we observed that Adjusted R square is 0.048 and is very small, hence fitting regression model is not appropriate. From regression analysis (ANOVA table) we have seen that overall regression is significant. that is whether lived poverty index depends on Southern Africa, East Africa, West Africa From table of coefficients, we observed that p- values are less than 0.05. hence the all three regressors are affects on lived poverty index.
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