Descriptive Statistics
Misty May Boring, Kristofer McHale, Barry Oosterhouse,
James Patton, Deborah Renton, and Christy Sirls
RES/341 Research and Evaluation I
October 18, 2010
Charles Fanning
Descriptive Statistics
The purpose of the research is to have an understanding of what affects home prices to enable buyers and sellers to make a sale or purchase. Analysis has supported that a house’s function of utility of various characteristics determines its residential real estate value (Besner, 2002). Numerous studies have been done using hedonic pricing models to determine the correlation between house characteristics, price, and salability. Spatial correlation, OLS regression, hedonic regression, and various coefficients are used to assess the effects of characteristics on house prices and salability.
This research will rank variables in order of importance for the salability of a house in the economic market of today. Those variables include the number of bedrooms the house has, the square footage, the distance from the center of the city, the number of baths, the township the house is in, if the house has a pool, and if the house has a garage. These variables are quantifiably measured and ranked by the percentage of occurrence compared to the total number of homes sold. In addition, this research will answer those variables that are worthy of consideration or inconsequential to the homeowner or prospective homebuyer.
Team D determined that 40 samples taken from a population size of 100,000 homes with the given variables: location, square footage, number of bedrooms, distance from center of city, and unique features such as a pool and garage will affect the salability of the homes in perspective markets. Team D evaluated the characteristics of the population and the relevance to the sample size to support the research process.
When determining how data can be used to support the hypothesis, each variable (price, beds, etc.) was used to...