Data Collection: Real Estate
Data Collection: Real Estate Data Collection: Real Estate The first portion of the study focused on identifying the problem, generating the hypothesis that the house in question requires negotiation, and completing a review of the data set. The premise relies on sale price being dependent on the number of bedrooms and bathrooms, square footage, the existence of a garage and pool, the district the home is located and the distance from the city.
Table 1.1: Variables Affecting Price [pic]
The study will continue by evaluating the data set provided to determine if a 3000 square-foot, six-bedroom house with a garage, pool, 3 baths located 15 miles from the city in district 4 substantiates a $398,900 price tag. The team will review similar research, define the sampling design, compile, and display the data so statistical analysis may follow.
Related Research Research suggests that external and internal factors both affect the sale price of a home. The National Center for Real Estate Research conducted a study using data from 1996 to 2006 for more than 28,800 residential property sales in and around Philadelphia (Bishop, 2004, p. 1). Hedonic regression served as the backbone for the statistical calculations for the study. Major findings of the study are outlined in Table 1.2.
Table 1.2: Attributes Effect on Sale Price (Bishop, 2004, p. 2)
|Attribute |Effect to price of home |
|Basement |Increase 9% |
|Additional 1,000 square feet |Increase 3.3% |
|In ground swimming pool |Increase 8% |
|Additional bathrooms |Increase 10-12% |
Table 1.1: Variables Affecting Price [pic]
The study will continue by evaluating the data set provided to determine if a 3000 square-foot, six-bedroom house with a garage, pool, 3 baths located 15 miles from the city in district 4 substantiates a $398,900 price tag. The team will review similar research, define the sampling design, compile, and display the data so statistical analysis may follow.
Related Research Research suggests that external and internal factors both affect the sale price of a home. The National Center for Real Estate Research conducted a study using data from 1996 to 2006 for more than 28,800 residential property sales in and around Philadelphia (Bishop, 2004, p. 1). Hedonic regression served as the backbone for the statistical calculations for the study. Major findings of the study are outlined in Table 1.2.
Table 1.2: Attributes Effect on Sale Price (Bishop, 2004, p. 2)
|Attribute |Effect to price of home |
|Basement |Increase 9% |
|Additional 1,000 square feet |Increase 3.3% |
|In ground swimming pool |Increase 8% |
|Additional bathrooms |Increase 10-12% |
References: Bond, M.T., Seiler, V.L., & Seiler, M.J. (2002). Residential real estate prices: A room with a view. Journal of Real Estate Research, 23, 129-138. Retrieved on January 19, 2009, from ProQuest database. Pratt, C. (2009, January 12). Homes still selling despite slump. McClatchy – Tribune Business News. Retrieved on January 19, 2009, from ProQuest database. Rosiers, F.D., Lagana, A., & Theriault, M. (2001, Jun). Size and proximity effects of primary schools on surrounding house values. Journal of Property Research, (18)2, 149. Retrieved on January 21, 2009, from EBSCOhost. Sekaran, U. (2003). Research methods for business: A skill-building approach (4th ed.). New York: Wiley, Inc.