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Regression Analysis to predict house prices in San Jose for year 2017

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Regression Analysis

Regression Analysis to predict house prices in San Jose for year 2017

Project Members

  • Jay Patel
  • Van Ahn Le

Abstract

The goal of this project is to predict the house prices of the San Jose city in summer 2017 based on the data collected from the summer 2016. The collected data is used to create several linear and non-linear models to predict the best house price in San Jose for summer 2017.

Environment

  • Matlab
  • Microsoft Excel

Theory Topics

  • Probability and Statistics
  • Linear Models/Regression

Results

The scatter plot matrix of all the variables used in the project. Scatter Plot Matrix

Pridiction of the house prices based on bedrooms, bathrooms and house size based on the regression analysis. Prediction Table

Referance

The data for the project was collected from the following website.

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