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Housing the Ultra-Poor - Theory and Practice in Haiti

The following is an economic case study. Based on your understanding of the ANOVA and utilizing the 5-step plus Hypothesis testing process, determine the F-calculation and the F-critical of the data attached. In addition, write a summary of the inference made based on the acceptance or rejection of your hypothesis statement. Please include facets of micro-economic theory. This information is attached.

A Model of Socio-Economic Differences

Housing the Ultra-Poor: Theory and Practice in Haiti

The following study was developed by Economist Simon Fass. Fass surveyed a sample population of low-income households in St. Martin. The variables analyzed were monthly income per adult and choice of rental contract for housing.

All families in St. Martin had to opt for one of 3 available time packages. They could pay in advance for a week, a month, or six months; and the shorter the time package, the higher the unit price. Payment by the week cost 10 to 20 percent more in monthly rent per square meter than payment by the month, and payment by the month cost twice as much as for 6 months. But offsetting the higher unit cost was the advantage of lower cash outlays. To obtain a week of housing required an average prepayment of $1.55. A month cost $5.30 and 6 months $18.90 (Fass, 1987)

You must determine if there is a difference among the income of the adults in respect to the housing contract they choose. Could the data of income be drawn from the same population or are we possibly looking at 2 or maybe 3 different sample population.


Fass, Simon. (1987). Housing the Ultra-Poor: Theory and Practice in Haiti. American Planning Association Journal, spring, pp. 193-205. Giventer, L.L. (1990). Statistical Analysis for Public Administration, (1), 11-20 to 11-21.

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Solution Summary

The solution provides a detailed discussion on the given problem and step-by-step method of performing Analysis of Variance or ANOVA Hypothesis Test on the given data. All the steps of hypothesis testing (formulation of null and alternate hypotheses, selection of significance level, choosing the appropriate test-statistic, decision rule, calculation of test-statistic and conclusion) have been explained in details. A separate Excel sheet showing the ANOVA analysis has also been included for better understanding.