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Chapter 3 discusses the principles of linear regression, including the use of ordinary least squares (OLS) for estimating parameters and the importance of the population regression function (PRF) and sample regression function (SRF). It outlines the assumptions necessary for OLS to be considered the best linear unbiased estimator (BLUE) and explains hypothesis testing for regression coefficients. Additionally, it covers the construction of confidence intervals for estimates and the distinction between testi

Author

Antonio Jose Luque Barcenas

Language

EN