April 2019
Beginner to intermediate
1240 pages
45h 43m
English
Content preview from Data Science for Business and Decision Making
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Chapter 15
Regression Models for Count Data: Poisson and Negative Binomial
Abstract
This chapter presents the regression models for count data (Poisson and negative binomial), establishing the circumstances based on which they can be used. The parameters for a Poisson regression model and negative binomial regression model are estimated by the maximum likelihood method. The results of the statistical tests pertinent to the Poisson and negative binomial regression models are evaluated. Confidence intervals of the estimated model parameters are also estimated for the purposes of prediction. Finally, the Poisson and negative binomial regression models are estimated in Microsoft Office Excel®, Stata Statistical Software®, and IBM SPSS Statistics ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.