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Forecasting real estate value using regression analysis

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1) Help Elaborate Purpose Statement 100-200 words

The dependent variable (Cost of the home in $) is determined by independent variables (Square footage, Number of bedrooms and Age)

The most important independent variable in this relationship is the Square footage because the Cost of the home in dollars is greatly influenced by the Square footage of the home.

2) Then Definition of Variables 100-200 Words

For each variable, write a single definition paragraph talking about the variable. Paragraphs should be in this order: dependent variable, primary independent variable, and three independent variables.

In addition to defining the independent variables, defend why each determines the dependent variable.

For the primary independent variable, at least two research sources that discuss the variable also must be cited. These sources need not be technical documents but should contain evidence to justify the relationship between the primary independent variable and the dependent variable. List these sources in the Works Cited (reference) page.

3) Data Description 100-200 words
For each of the variables, at least 30 observations of cross-sectional data must be obtained. Thus for the final research paper, a data matrix that is at least 30 rows by numbers of variables must be presented.
In one paragraph, identify the data sources and describe the data (i.e., which government agencies supply the data, which methods are used to compile them, when they were collected, etc.).

4) Works Cited Page
The final page of the proposal should be a Works Cited page listing the two research sources for the primary independent variable and the data sources, with a separate citation for each table of data, including specific table numbers for each of the sources.

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Solution Summary

Shows how to study and report a comprehensive problem using regression analysis. This paper can be used by students as a guideline for them to work on similar papers.

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Please see the attached file.

FORECASTING THE REAL ESTATE VALUE: METHODOLOGY USING REGRESSION ANALYSIS

1. Introduction
The durability, fixity and heterogeneity of attributes in real estate properties leads to not only costly search to uncover the prices and attributes of property but also high transaction costs in real estate market as compared to financial markets and other commodity markets. The many frictions associated with the purchase of real estate makes it hard to assess the correct value of the home. However, the prior research has provided ...

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