A Comparison of Three Estimation Methods In Linear Regression Analysis

摘要

The paper begins with an introduction of some crucial definitions apropos of regression analysis. Then it discusses briefly the concept of R-square that verifies the accuracy of a regression model and of Hypothesis Testing that tests hypothesis made concerning the population. The main part of the paper then focuses on three estimation methods that estimate the parameters of a regression model: Ordinary Least Square, Method of Moments, and Maximum Likelihood Estimation. The paper concludes with a discussion on the advantages and disadvantages of each method and the possible applications of linear regression.