Predictive regression analysis of housing price in Iowa

Thesis title: Predictive regression analysis of housing price in Iowa
Author: Guo, Zhida
Thesis type: Diploma thesis
Supervisor: Helman, Karel
Opponents: Čabla, Adam
Thesis language: English
Abstract:
This thesis presents an analysis of predictive modeling techniques and outlier detection methods in the context of real estate sale price prediction. The study aims to find an optimal regression model by integrating variable selection procedures, influential observation removal, and regression outlier detection, and understand the impacts of different variable selection methods. The investigation, conducted on a real-world housing dataset, evaluates the models using metrics such as Mean Square Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE).
Keywords: cross validation; prediction; empirical analysis; Regression analysis
Thesis title: PREDICTIVE REGRESSION ANALYSIS OF HOUSING PRICE IN IOWA
Author: Guo, Zhida
Thesis type: Diplomová práce
Supervisor: Helman, Karel
Opponents: Čabla, Adam
Thesis language: English
Abstract:
This thesis presents an analysis of predictive modeling techniques and outlier detection methods in the context of real estate sale price prediction. The study aims to find an optimal regression model by integrating variable selection procedures, influential observation removal, and regression outlier detection, and understand the impacts of different variable selection methods. The investigation, conducted on a real-world housing dataset, evaluates the models using metrics such as Mean Square Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE).
Keywords: regression analysis; prediction; cross validation; empirical analysis

Information about study

Study programme: Economic Data Analysis/Data Analysis and Modeling
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Informatics and Statistics
Department: Department of Statistics and Probability

Information on submission and defense

Date of assignment: 21. 6. 2021
Date of submission: 4. 12. 2023
Date of defense: 21. 8. 2024
Identifier in the InSIS system: https://insis.vse.cz/zp/77243/podrobnosti

Files for download

    Last update: