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Analysis of Case 28 Housing Prices II
GM 533: Managerial Statistics
Daniela Jaimes
Freddy Plazas
Professor: Talal HajHamdo
February 20, 2012

Table of Contents
Summary………………………………………………………………………………………...3
Background Analysis……………………………………………………………………………4
Purpose of the Study ……………………………………………………………………………5
Data Analysis..…….……………………………………………………………………………..5
Results…………………………………………………………………………………………...9
Conclusions……………………………………………………………….…………………….16
References.....…….…..…………………………………………………………………………18
Appendices …………..…………………………………………………………………………19

Analysis of Case 28: Housing Prices II
Investigations in general usually have several descriptive variables. For example, for demonstrating mental disease, potential predictors include salary, educational accomplishment, an index of life events, social and environmental stress, marital status, age, self-assessment of health, number of jobs held in previous years, number of relatives who live nearby, number of close friends, membership in social organizations, frequency of church attendance, and so forth .
Typically, the regression model for the study includes some explanatory variables for hypothetical reasons. Others may be included for experimental purposes, to check whether they explain much variation in the response variable. The model might also include terms to allow for interactions. In such situations, it can be difficult to decide which variables to use and which to exclude (Benjamin, Guttery, & Sirmans, 2004). However, the Regression Model allows the researcher to determine which variables are significant and which are not related with the studied process.
Summary
In this analysis we will use a multiple regression analysis method to predict the appropriate selling price of our home located in Eastville, Oregon.   This methodology is a statistical analysis that will explain the correlation between several characteristics related with the house, using those features as independent...

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