Practical Regression: Maximum Likelihood Estimation Case Solution And Analysis, HBR Case Study Solution & Analysis of Harvard Case Studies

This is the eighth in a series of lecture notes which, if tied together into a textbook, might be entitled "Practical Regression." The objective of the notes would be to supplement the theoretical content of most statistics texts with practical advice based on nearly three decades of expertise of the writer, combined with over one hundred years of experience of colleagues who have offered guidance.

As the title "Practical Regression" implies, these notes are a guide to performing regression in practice. The note explains the idea of goodness of fit and why MLE is a powerful choice to R-squared. The note follows the computation of the odds score as well as an easy example that acquires the intuition of MLE and also the algorithm used to estimate coefficients in MLE models.

Practical Regression Maximum Likelihood Estimation Case Study Solution

PUBLICATION DATE: May 14, 2012 PRODUCT #: KEL642-HCB-ENG

This is just an excerpt. This case is about FINANCE & ACCOUNTING