Research Real Estate Data Set

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Abstract
In this paper the team analyzed three scholarly articles relating to our study. Furthermore, the team also analyzed additional data sets to include more variables like bedrooms and bathrooms in our investigation to test our hypothesis which shows that the results are consistent with the hypothesis. The population size, primary and secondary data, using unbiased information and applying ethics are also discussed in detail.

Real Estate Data Set II
As we begin the final stages of our project it is important to understand the process of applied research and how one or more variable have an impact on the dependable variable. It is important to understand why research is necessary and how we apply research to get answers to issues. The team analyzed thirty date sets to research homes with or without a pool, with or without a garage, and on the proximity of the house to the city, and how those factors affected the selling prices of homes. Furthermore, the team also analyzed more data sets to include more variables like bedrooms and bathrooms. Six bedrooms, three bath houses will sell for more than a one bedroom, one bath houses, regardless of whether it has a pool or garage. As we go forward with this assignment and analyze more data collection sets, it seems that the hypothesis that we proposed is the right one. Our hypothesis is based around the concept of human prioritization and its role in home selection. Additionally, the team researched three scholarly articles that are pertinent to our study to help us understand why the research is important and necessary.

The first article uses analysis to discuss the connection between the selling price of a home and “Time on the Market” (TOM) (Sirmans, et al, 2010). It states that the longer the house is on the market the lower the selling price of the house. The study uses data sets to examine single family homes and whether the TOM co-efficient is susceptible to location, income of families, wealth and time. The results proved that the TOM co-efficient is sensitive to the variables and there is a significant relationship between TOM and the selling prices (Sirmans et al, 2010). It also states that selling prices and TOM is a very complicated because sellers / buyers want to maximize the price, while sellers want to sell at the top price buyers want to purchase at the lowest price.

The second article discusses the study of how technology of real estate is changing and how important technology is key to gather important data from private and public sources for the real estate industry. Many studies have been published about the impact of the information on the real estate industry, on market size and efficiency, and market innovation. These studies have proven that email and the use of internet are used as a positive marketing tool. Survey questions were developed to gather information about real estate agents and their attitude about using information technology as marketing their services. The results were positive and all that were surveyed viewed that information technology was key in some areas. Internet usage got a high score along with online research but personal webpage’s indicated a lower score (Acharya et al, 2010).

The third article examined that in real estate development there is a need for risk assessment techniques to assess the impact of the project. The article is based on an exploratory survey which data was collected through interviews and a questionnaire. The study was conducted in the Thailand area using Thai real estate development companies. The study revealed that there are no systematic techniques to deal with the concerns of economic and political risks (Khumpaisal et al, 2010). All three articles focus on real estate research and how information is collected and used in different studies. All three article discuss how data, the collection of the data and the usage of the data play an important part while...
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