Informações sobre o curso
4.4
2,119 ratings
375 reviews
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing....
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Sugerido: 5 hours/week

Aprox. 17 horas restantes
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English

Legendas: English

O que você vai aprender

  • Check
    Describe novel uses of regression models such as scatterplot smoothing
  • Check
    Investigate analysis of residuals and variability
  • Check
    Understand ANOVA and ANCOVA model cases
  • Check
    Use regression analysis, least squares and inference

Habilidades que você terá

Regression AnalysisLinear RegressionGeneralized Linear ModelModel Selection
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Clock

Sugerido: 5 hours/week

Aprox. 17 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
12 horas para concluir

Week 1: Least Squares and Linear Regression

This week, we focus on least squares and linear regression....
Reading
9 vídeos (Total de 74 min), 11 leituras, 4 testes
Video9 videos
Introduction: Basic Least Squares6min
Technical Details (Skip if you'd like)2min
Introductory Data Example12min
Notation and Background7min
Linear Least Squares6min
Linear Least Squares Coding Example7min
Technical Details (Skip if you'd like)11min
Regression to the Mean11min
Reading11 leituras
Welcome to Regression Models10min
Book: Regression Models for Data Science in R10min
Syllabus10min
Pre-Course Survey10min
Data Science Specialization Community Site10min
Where to get more advanced material10min
Regression10min
Technical details10min
Least squares10min
Regression to the mean10min
Practical R Exercises in swirl Part 110min
Quiz1 exercício prático
Quiz 120min

2

Seção
Clock
11 horas para concluir

Week 2: Linear Regression & Multivariable Regression

This week, we will work through the remainder of linear regression and then turn to the first part of multivariable regression....
Reading
10 vídeos (Total de 70 min), 5 leituras, 4 testes
Video10 videos
Interpreting Coefficients3min
Linear Regression for Prediction10min
Residuals5min
Residuals, Coding Example14min
Residual Variance7min
Inference in Regression5min
Coding Example6min
Prediction9min
Really, really quick intro to knitr3min
Reading5 leituras
*Statistical* linear regression models10min
Residuals10min
Inference in regression10min
Looking ahead to the project10min
Practical R Exercises in swirl Part 210min
Quiz1 exercício prático
Quiz 220min

3

Seção
Clock
13 horas para concluir

Week 3: Multivariable Regression, Residuals, & Diagnostics

This week, we'll build on last week's introduction to multivariable regression with some examples and then cover residuals, diagnostics, variance inflation, and model comparison. ...
Reading
14 vídeos (Total de 168 min), 5 leituras, 5 testes
Video14 videos
Multivariable Regression part II10min
Multivariable Regression Continued8min
Multivariable Regression Examples part I19min
Multivariable Regression Examples part II22min
Multivariable Regression Examples part III7min
Multivariable Regression Examples part IV7min
Adjustment Examples17min
Residuals and Diagnostics part I5min
Residuals and Diagnostics part II9min
Residuals and Diagnostics part III9min
Model Selection part I7min
Model Selection part II22min
Model Selection part III12min
Reading5 leituras
Multivariable regression10min
Adjustment10min
Residuals10min
Model selection10min
Practical R Exercises in swirl Part 310min
Quiz2 exercícios práticos
Quiz 314min
(OPTIONAL) Data analysis practice with immediate feedback (NEW! 10/18/2017)8min

4

Seção
Clock
17 horas para concluir

Week 4: Logistic Regression and Poisson Regression

This week, we will work on generalized linear models, including binary outcomes and Poisson regression. ...
Reading
7 vídeos (Total de 95 min), 6 leituras, 6 testes
Video7 videos
GLMs21min
Logistic Regression part I17min
Logistic Regression part II3min
Logistic Regression part III8min
Poisson Regression part I12min
Poisson Regression part II12min
Hodgepodge18min
Reading6 leituras
GLMs10min
Logistic regression10min
Count Data10min
Mishmash10min
Practical R Exercises in swirl Part 410min
Post-Course Survey10min
Quiz1 exercício prático
Quiz 412min
4.4
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Melhores avaliações

por MMMar 13th 2018

Great course, very informative, with lots of valuable information and examples. Prof. Caffo and his team did a very good job in my opinion. I've found very useful the course material shared on github.

por KADec 17th 2017

Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.

Instrutores

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Sobre Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

Sobre o Programa de cursos integrados Data Science

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material....
Data Science

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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