Probability and Statistics

Este curso forma parte de Programa Especializado - Data Science

Regression Models

ofrecido por

Programa especializado Data Science

Johns Hopkins University

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....

Curso 7 de 10 en

Programa especializado Data Science

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Sugerido: 5 hours/week

Aprox. 17 horas para completar

English

Subtítulos: English

Qué aprenderás

Describe novel uses of regression models such as scatterplot smoothing

Investigate analysis of residuals and variability

Understand ANOVA and ANCOVA model cases

Use regression analysis, least squares and inference

Habilidades que obtendrás

Regression AnalysisLinear RegressionModel SelectionGeneralized Linear Model

Curso 7 de 10 en

Programa especializado Data Science

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Sugerido: 5 hours/week

Aprox. 17 horas para completar

English

Subtítulos: English

Programa - Qué aprenderás en este curso

1

Sección

12 horas para completar

Week 1: Least Squares and Linear Regression

This week, we focus on least squares and linear regression....

9 videos (Total: 74 min), 11 readings, 4 quizzes

9 videos

Introduction to Regression6m

Introduction: Basic Least Squares6m

Technical Details (Skip if you'd like)2m

Introductory Data Example12m

Notation and Background7m

Linear Least Squares6m

Linear Least Squares Coding Example7m

Technical Details (Skip if you'd like)11m

Regression to the Mean11m

11 lecturas

Welcome to Regression Models10m

Book: Regression Models for Data Science in R10m

Syllabus10m

Pre-Course Survey10m

Data Science Specialization Community Site10m

Where to get more advanced material10m

Regression10m

Technical details10m

Least squares10m

Regression to the mean10m

Practical R Exercises in swirl Part 110m

1 ejercicio de práctica

Quiz 120m

2

Sección

11 horas para completar

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....

10 videos (Total: 70 min), 5 readings, 4 quizzes

10 videos

Statistical Linear Regression Models2m

Interpreting Coefficients3m

Linear Regression for Prediction10m

Residuals5m

Residuals, Coding Example14m

Residual Variance7m

Inference in Regression5m

Coding Example6m

Prediction9m

Really, really quick intro to knitr3m

5 lecturas

*Statistical* linear regression models10m

Residuals10m

Inference in regression10m

Looking ahead to the project10m

Practical R Exercises in swirl Part 210m

1 ejercicio de práctica

Quiz 220m

3

Sección

13 horas para completar

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. ...

14 videos (Total: 168 min), 5 readings, 5 quizzes

14 videos

Multivariable Regression part I9m

Multivariable Regression part II10m

Multivariable Regression Continued8m

Multivariable Regression Examples part I19m

Multivariable Regression Examples part II22m

Multivariable Regression Examples part III7m

Multivariable Regression Examples part IV7m

Adjustment Examples17m

Residuals and Diagnostics part I5m

Residuals and Diagnostics part II9m

Residuals and Diagnostics part III9m

Model Selection part I7m

Model Selection part II22m

Model Selection part III12m

5 lecturas

Multivariable regression10m

Adjustment10m

Residuals10m

Model selection10m

Practical R Exercises in swirl Part 310m

2 ejercicios de práctica

Quiz 314m

(OPTIONAL) Data analysis practice with immediate feedback (NEW! 10/18/2017)8m

4

Sección

17 horas para completar

Week 4: Logistic Regression and Poisson Regression

This week, we will work on generalized linear models, including binary outcomes and Poisson regression. ...

7 videos (Total: 95 min), 6 readings, 6 quizzes

7 videos

GLMs21m

Logistic Regression part I17m

Logistic Regression part II3m

Logistic Regression part III8m

Poisson Regression part I12m

Poisson Regression part II12m

Hodgepodge18m

6 lecturas

GLMs10m

Logistic regression10m

Count Data10m

Mishmash10m

Practical R Exercises in swirl Part 410m

Post-Course Survey10m

1 ejercicio de práctica

Quiz 412m

Instructores

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

Acerca de 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....

Acerca del programa especializado 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....

Preguntas Frecuentes

When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
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.
What is the refund policy?
Is financial aid available?

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Regression Models

Curso 7 de 10 en

Cursos 100 % en línea

Fechas límite flexibles

Sugerido: 5 hours/week

English

Qué aprenderás

Habilidades que obtendrás

Curso 7 de 10 en

Cursos 100 % en línea

Fechas límite flexibles

Sugerido: 5 hours/week

English

Programa - Qué aprenderás en este curso

1

Week 1: Least Squares and Linear Regression

2

Week 2: Linear Regression & Multivariable Regression

3

Week 3: Multivariable Regression, Residuals, & Diagnostics

4

Week 4: Logistic Regression and Poisson Regression

22%

83%

14%

Principales revisiones

Instructores

Brian Caffo, PhD

Roger D. Peng, PhD

Jeff Leek, PhD

Acerca de Johns Hopkins University

Acerca del programa especializado Data Science

Preguntas Frecuentes