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# Generalized Linear Models in R

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Comience El Curso Gratis
4 Horas14 Videos51 Ejercicios
18.305 AprendicesDeclaración de cumplimiento

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## Descripción del curso

Linear regression serves as a workhorse of statistics, but cannot handle some types of complex data. A generalized linear model (GLM) expands upon linear regression to include non-normal distributions including binomial and count data. Throughout this course, you will expand your data science toolkit to include GLMs in R. As part of learning about GLMs, you will learn how to fit model binomial data with logistic regression and count data with Poisson regression. You will also learn how to understand these results and plot them with ggplot2.
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1. 1

### GLMs, an extension of your regression toolbox

Gratuito

This chapter teaches you how generalized linear models are an extension of other models in your data science toolbox. The chapter also uses Poisson regression to introduce generalize linear models.

Reproducir Capítulo Ahora
Limitations of linear models
50 xp
Assumptions of linear models
50 xp
Refresher on fitting linear models
100 xp
Poisson regression
50 xp
Fitting a Poisson regression in R
100 xp
Comparing linear and Poisson regression
100 xp
Intercepts-comparisons versus means
100 xp
Basic lm() functions with glm()
50 xp
Applying summary(), print(), and tidy() to glm
100 xp
Extracting coefficients from glm()
100 xp
Predicting with glm()
100 xp
2. 3

### Interpreting and visualizing GLMs

This chapter teaches you about interpreting GLM coefficients and plotting GLMs using ggplot2.

3. 4

### Multiple regression with GLMs

In this chapter, you will learn how to do multiple regression with GLMs in R.

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Sets De Datos

Bus Commuter dataset

Richard Erickson

Data Scientist

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