Housing Prices in Blowing Rock, NC:
A Hedonic Analysis

Thomas Carter

Economics 4000

1. Introduction
A difficult characteristic to understand about the housing market is how a price is given for a particular house. That price will be designated to that particular house alone. All houses have various pricing, so I can’t always assume that one will cost more or less than any other. The pricing for houses vary based on their characteristics. Each characteristic must be analyzed to determine its contribution or detraction toward the price. I have taken some of these characteristics and modeled the relationship between them and the price of real estate for a specific area.

How are these characteristics used in determining the price? A model that is commonly used in real estate appraisal is the hedonic regression. This method is specific to breaking down items that are not homogenous commodities, to estimate value of its characteristics and ultimately determine a price based on the consumers’ willingness to pay. The approach in estimating the values is done by measuring the differences in the price of certain goods with regards to specific location. E.g. average cost of real estate is much lower in Missouri than in California. Location may be the biggest factor in real estate pricing.

2. Data and Regression Analysis
My data is for Blowing Rock, NC. It’s a resort town in the Blue Ridge Mountains. The attractions here are mostly outdoor activities taking place in the secluded wilderness. The population is only about 1500 and the average cost of a house from my data is $485,839.50.

For my linear regression, I am modeling the relationship between the price of homes, being my dependent variable, and some characteristics of the homes, being my explanatory variables. Originally my data consisted of the following for real estate in Blowing Rock, NC: price - selling price, miles from central business district, number of bedrooms, number of full bathrooms,...

...LinearRegression deals with the numerical measures to express the relationship between two variables. Relationships between variables can either be strong or weak or even direct or inverse. A few examples may be the amount McDonald’s spends on advertising per month and the amount of total sales in a month. Additionally the amount of study time one puts toward this statistics in comparison to the grades they receive may be analyzed using the...

.... The following sample observations were randomly selected.
X: 5 3 6 3 4 4 6 8
Y: 13 15 7 12 13 11 9 5
a. Determine the coefficient of correlation.
b. Determine the coefficient of determination.
c. Interpret the result.
. The following sample observations were randomly selected.
X: 5 3 6 3 4 4 6 8
Y: 13 15 7 12 13 11 9 5
a. Determine the coefficient of correlation.
b. Determine the coefficient of determination.
c. Interpret the result.
. The following sample observations...

...Linear -------------------------------------------------
Important
EXERCISE 27 SIMPLE LINEARREGRESSION
STATISTICAL TECHNIQUE IN REVIEW
Linearregression provides a means to estimate or predict the value of a dependent variable based on the value of one or more independent variables. The regression equation is a mathematical expression of a causal proposition emerging from a theoretical framework. The...

...Linear-Regression Analysis
Introduction
Whitner Autoplex located in Raytown, Missouri, is one of the AutoUSA dealerships. Whitner Autoplex includes Pontiac, GMC, and Buick franchises as well as a BMW store. Using data found on the AutoUSA website, Team D will use LinearRegression Analysis to determine whether the purchase price of a vehicle purchased from Whitner Autoplex increases as the age of the consumer purchasing the vehicle...

...
A. DETERMINE IF BLOOD FLOW CAN PREDICT ARTIRIAL OXYGEN.
1. Always start with scatter plot to see if the data is linear (i.e. if the relationship between y and x is linear). Next perform residual analysis and test for violation of assumptions. (Let y = arterial oxygen and x = blood flow).
twoway (scatter y x) (lfit y x)
regress y x
rvpplot x
2. Since regression diagnostics failed, we transform our data.
Ratio transformation was used...

...retailers behavior towards Aircel in selected region. The data is collected directly by visiting outlets through structured interview scheduled. The statistical tools used to analyze the data are: Co-relation analysis, Simple LinearRegression and Multiple LinearRegression. The software used to analyze the data is Windostat version 8.6, developed by Indostat services, is an advanced level statistical software for research and...

...Chapter 13
LinearRegression and Correlation
True/False
1. If a scatter diagram shows very little scatter about a straight line drawn through the plots, it indicates a rather weak correlation.
Answer: False Difficulty: Easy Goal: 1
2. A scatter diagram is a chart that portrays the correlation between a dependent variable and an independent variable.
Answer: True Difficulty: Easy Goal: 1 AACSB: AS
3....

...
Linearregression is a crucial tool in identifying and defining key elements influencing data. Essentially, the researcher is using past data to predict future direction. Regression allows you to dissect and further investigate how certain variables affect your potential output. Once data has been received this information can be used to help predict future results. Regression is a form of forecasting that determines the value of...

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