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The home characteristics can further be classified into ‘the number of rooms in a house’, ‘the number of full and half bath rooms’, ‘availability of garage’, ‘cellar’, ‘balcony’ etc. Similarly, the characteristics related to the vicinity or the neighborhood of a house can be termed as the neighborhood characteristics. These characteristics can further be classified into ‘roadside’, ‘traffic intensity’, ‘bothersome location’, ‘crime prone vicinity’ etc. The scope of this paper is to consider given factors for the assessment of house value by testing the level of their significance.
The expected outcome is termed as a prediction model. INTRODUCTION The assessment of the price of a house is generally assessed through the few apparent factors like the construction value, design and location of the house. The rough estimation usually does not encompass the related factors that are important to decide the value of a house and have a significant impact on the assessment process. The study of the factors other than the common factors is important to identify their role in the determination of the price or value of a home.
Generally a realtor’s claim would always be that the location is the most important factor when it comes to determining the value of a house or home. . The null hypothesis here would be the realtor’s claim i.e. the location is the most important factor in assessing the house value whereas the alternate hypothesis refutes by stating that this is not the only factor but there are other significantly effective factors that are needed to be taken into account. LITERATURE REVIEW There are a number of processes that can be used to predict house values.
These include various probabilistic methods. Multivariate Spatial Method, Time Series analysis, Footy Forecast Forecasting methods( a method that is similar to simple sequence method), ordinary least square regression and logistic regression, ‘hedonic model and artificial neural network model’, ‘non-parametric latent manifold model’. The procedure that we would incorporate in order to evaluate the house values from our system is multiple regression analysis. Multiple Regression Analysis incorporates the effects that a number of independent variables have on a dependent variable.
In the current study it is attempted to evaluate that what do independent variables such as the number of bedrooms and bathrooms present in a house, the vicinity of the house and other factors etc. have of the value of a house. Home characteristics The properties related to the home structure, architecture, design and construction quality and the provisions it extends are considered to come under home characteristics. The main characteristics included in this study are the size in square feet, number of bedrooms and bath rooms, presence of pool and fireplace, age of house and design of construction.
Neighborhood characteristics The outside environment of a home generally referred to as location comprises of the neighborhood characteristics. The study includes
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