Gm 533 Course Project

In: Business and Management

Submitted By chloe5384
Words 1503
Pages 7
To: Board of Directors
From:
Date: 8/20/10
Subject: Analysis of Pricing Data

As you asked, I have analyzed the data and concluded the selling price model of houses in Eastville. Here are my results. Data: Data was provided of a sample of 108 chosen houses in Eastville, Oregon. From these files, we obtained variables including: total square footage of the house, numbers of beds and baths, style of the house, presence of gas forced or electric heat, garage, basement, age of house, fire place, and school district. In order to examine what the selling price model of houses in Eastville, Oregon is, we also need to figure out the factors drive the selling price. Hypothesis: • The higher the total square footage of the house is, the higher the selling price will be. • The more bedrooms there are, the higher the selling price will be. • The more bathrooms there are, the higher the selling price will be. • The style of the design accommodates for the selling price of the house. • The presence of electric heat will result in a higher selling price. • The presence of a 2 car garage will result in a higher selling price. • The presence of a fireplace will result in a higher selling price. • Since Apple Valley School district is the more preferable, houses in this district will result in a higher selling price. • The older the house is, the lower the selling price will be. Results: Using Price as the independent variable, and all other factors as independent variables, a regression analysis was ran to understand the factors involved in the selling price of houses in Eastville. Explanation: The ANOVA table shows that the value of the p-value (0.00) is less than 0.05, which means that the model is significant. The ANOVA analysis denotes if the hypothesis is significant or not. In this analysis R^2 =…...

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