Research Real Estate Data Set

10 October 2016

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.

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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 ellers / 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 conducting research.

When conducting research it is often difficult, or impractical to test the entire population. Many issues can arise, such as time consumption, cost, and redundant information. Often it is possible for researchers to draw conclusions based on population samples. This is when we test a small portion of the population and draw conclusions on the entire population based on the sample results. For our research the sample of thirty homes came from a larger sample of one hundred six homes. These homes were a sample of homes in one state, across five townships.

For our research we decided to limit the sample to around thirty homes of similar qualities (outside of the variables we are testing). The reason we do this is to be sure there isn’t an outside, unknown variable affecting the experiment. Therefore we chose homes that are between two and three bedrooms, with two bathrooms. This gave us a sample of thirty-one homes. For this particular research, it is possible to see the affects of different variables on home prices. Also, with more than thirty samples it is also possible to eliminate outliers that may skew averages.

For example, if we only tested three homes and two of them were priced outrageously, we wouldn’t be able to draw valid conclusions. However, by testing thirty-one homes, we can eliminate outliers. There are many possible sources of bias and error when testing a hypothesis with only sample of the population. In our case, we could simply omit homes that disprove our hypothesis. One reason for this is if we were working for a real estate company and they want to see which homes can make them the most money, and we know there are a lot of homes near the city center for sale.

If we omit homes far away from the city that are selling for more, our bias has caused us to give false findings. Not all omissions are intentional. Sometimes errors are simply made in the research process. For example, with our research we could have included homes with any number of bedrooms. This would have resulted in data that may not have been practical for our research. For example, the complete data set included homes with up to eight bedrooms. If we were to compare that to a home with only two bedrooms the fact that either had a pool, or garage, or was close to the city would have been negligible.

Again, we chose to only test similar homes in respect to number of bedrooms and bathrooms in order to prevent this error. It is necessary to collect primary data when a researcher cannot find the data needed in secondary sources. Some methods of primary research would include observation, postal surveys, telephone interviews, online surveys, face to face surveys, focus groups, and test marketing. Observation works well in retail markets. Observing consumer behavior provides many insights, although can sometimes leave unanswered questions.

Postal surveys are great because they are relatively cheap with the ability to cover a wide geographical area. However, response rates are minimal and can take quite some time before any of the surveys are returned. Telephone interviews allow quicker feedback than a postal survey but any potential customers are usually hesitant on giving anything but short answers. Increasingly popular and at relatively low cost, surveys online are widely used by growing businesses as a way of gathering the views of potential and existing customers.

Face to face surveys are sometimes costly, but a great way to get individual detailed insight, while focus groups are a good way of getting detailed information about customer preferences and tastes. Test marketing involves picking a small section of the market and selling a new product in order to assess customer reaction. This primary research can be a great predictor of how a new product or service will be received by the larger market. Primary research is the preferred research and conducted all of the time.

National polls and surveys collect the population’s thoughts about proposals or particular political figures, journalists use it as their primary means of reporting events as well as news, and organizations collect data on their market trends and consumer base. When conducting research in professional or academic settings, the researcher needs to be aware of the ethics behind the research activity Ethical issues arise throughout any piece of all research. These issues often turn into political ones, and there are also close connections between issues around participation and ethical concerns.

Ethical issues also have a tendency to turn into questions of trust. The researcher is the research instrument therefore the reader and/or user of qualitative research must be able to trust the researcher to have followed the proper procedures. There are quite a few key phrases which describe the system of ethical protections that medical research and the contemporary social establishments have created such as, voluntary participation, informed consent, confidentiality, anonymity, and rights to service, to better protect the research participant’s rights.

When conducting research it is important to understand all stages of the research and apply good practices such as using unbiased sources and clear and ethical standards. Even when clear ethical standards and principles are in place, there will be times when the rights of potential participants runs up against the need to do accurate research. No set of standards can possibly anticipate every ethical circumstance. Furthermore, there needs to be a procedure that assures that researchers will consider all relevant ethical issues in formulating research plans.

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