Real Estate Research Process
RES 341 / Research and Evaluation 1
March 28, 2011
Real Estate Research Process
Every individual whether they are aware of it or not, base their decision-making on some form of statistical data. Simple everyday decisions are made through rationalizing a problem or opportunity, forming a hypothesis, analyzing information, and determining a decision based on the gathered information. For the purpose of practicality, Team A has chosen real estate market data gathered from the website for the Statistical Techniques in Business and Economics (2008) textbook to formulate and define a chosen problem, attempt to delineate the ...view middle of the document...
Problem Definition and Research Hypothesis
After gathering the data, the research team has to define the issue of the concern or question more clearly. Sekaran (2003) defines the step of problem definition as a precise statement of the issue or question and to find an answer or solution. The question from the real estate data is “Does the price of a house depend on its size and its number of bedrooms?”
Once the problem statement is defined, the next step in the research process is to formulate a hypothesis. Sekaran (2003) stated, “A hypothesis is a logically conjectured relationship between two or more variables expressed in the form of a testable statement” (p. 103). The students in Team A chose the following hypothesis: “The bigger the square footage of a house and the more bedrooms a house has, the more expensive is the price of a house.” They will look at the real estate data from 2005 to determine if the size of a house or the number of bedrooms relate to the price of a house. At the end of this research the authors of this paper will either confirm if their hypothesis is true or false.
The first possible outcome is that the price does not depend on the size of the house, but that the price depends on the location of the particular real estate. The locality can be related to several factors. An example of location factors is if the house is in a downtown location or suburb, if it is on the water or what state the house is located in. Another possible outcome of this research is that the price of a dwelling depends on the additional attributes of the house. Examples of these attributes would be if a house has a garage or a pool. A pool has nothing to do with the size of a house; however, a buyer may be willing to spend more for this amenity. A third outcome is the verification of the hypothesis stated above. The price of a house depends on the number of bedrooms and the size of the house. These are three examples of possible outcomes on the real estate research.
Operational Definition of Each Variable
To validate the hypothesis, the team has to measure the different variables. An operational definition describes the observable characteristics to measure the concept (Sekaran, 2003). In the case of the real estate data, the variables are the price, size, and the number of bedrooms in a residence. These variables have physical measurements that can be easily verified.
Measurement Scale for Each Variable
Accordingly, to test the hypothesis, the variables that will be analyzed will be the selling price of the house, the square-footage size of the house, and the number of bedrooms of the house. These are the intervals encompassed in Team A’s hypothesis. However, Team A will also measure other variables connected to outcomes not stated in the hypothesis, such location (for instance distance and time from house to center of town) and desirable amenities.
To test the above-mentioned variables Team A will need to select specific...