课程信息
4.4
2,238 个评分
393 个审阅
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....
Stacks

Course 7 of 10 in the

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100% 在线课程

立即开始,按照自己的计划学习。
Calendar

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Clock

Approx. 17 hours to complete

建议:5 hours/week...
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您将学到的内容有

  • 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

您将获得的技能

Model SelectionGeneralized Linear ModelLinear RegressionRegression Analysis
Stacks

Course 7 of 10 in the

Globe

100% 在线课程

立即开始,按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Clock

Approx. 17 hours to complete

建议:5 hours/week...
Comment Dots

English

字幕:English, Vietnamese...

教学大纲 - 您将从这门课程中学到什么

Week
1
Clock
完成时间为 12 小时

Week 1: Least Squares and Linear Regression

This week, we focus on least squares and linear regression....
Reading
9 个视频(共 74 分钟), 11 个阅读材料, 4 个测验
Video9 个视频
Introduction: Basic Least Squares6分钟
Technical Details (Skip if you'd like)2分钟
Introductory Data Example12分钟
Notation and Background7分钟
Linear Least Squares6分钟
Linear Least Squares Coding Example7分钟
Technical Details (Skip if you'd like)11分钟
Regression to the Mean11分钟
Reading11 个阅读材料
Welcome to Regression Models10分钟
Book: Regression Models for Data Science in R10分钟
Syllabus10分钟
Pre-Course Survey10分钟
Data Science Specialization Community Site10分钟
Where to get more advanced material10分钟
Regression10分钟
Technical details10分钟
Least squares10分钟
Regression to the mean10分钟
Practical R Exercises in swirl Part 110分钟
Quiz1 个练习
Quiz 120分钟
Week
2
Clock
完成时间为 11 小时

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 个视频(共 70 分钟), 5 个阅读材料, 4 个测验
Video10 个视频
Interpreting Coefficients3分钟
Linear Regression for Prediction10分钟
Residuals5分钟
Residuals, Coding Example14分钟
Residual Variance7分钟
Inference in Regression5分钟
Coding Example6分钟
Prediction9分钟
Really, really quick intro to knitr3分钟
Reading5 个阅读材料
*Statistical* linear regression models10分钟
Residuals10分钟
Inference in regression10分钟
Looking ahead to the project10分钟
Practical R Exercises in swirl Part 210分钟
Quiz1 个练习
Quiz 220分钟
Week
3
Clock
完成时间为 13 小时

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 个视频(共 168 分钟), 5 个阅读材料, 5 个测验
Video14 个视频
Multivariable Regression part II10分钟
Multivariable Regression Continued8分钟
Multivariable Regression Examples part I19分钟
Multivariable Regression Examples part II22分钟
Multivariable Regression Examples part III7分钟
Multivariable Regression Examples part IV7分钟
Adjustment Examples17分钟
Residuals and Diagnostics part I5分钟
Residuals and Diagnostics part II9分钟
Residuals and Diagnostics part III9分钟
Model Selection part I7分钟
Model Selection part II22分钟
Model Selection part III12分钟
Reading5 个阅读材料
Multivariable regression10分钟
Adjustment10分钟
Residuals10分钟
Model selection10分钟
Practical R Exercises in swirl Part 310分钟
Quiz2 个练习
Quiz 314分钟
(OPTIONAL) Data analysis practice with immediate feedback (NEW! 10/18/2017)8分钟
Week
4
Clock
完成时间为 17 小时

Week 4: Logistic Regression and Poisson Regression

This week, we will work on generalized linear models, including binary outcomes and Poisson regression. ...
Reading
7 个视频(共 95 分钟), 6 个阅读材料, 6 个测验
Video7 个视频
GLMs21分钟
Logistic Regression part I17分钟
Logistic Regression part II3分钟
Logistic Regression part III8分钟
Poisson Regression part I12分钟
Poisson Regression part II12分钟
Hodgepodge18分钟
Reading6 个阅读材料
GLMs10分钟
Logistic regression10分钟
Count Data10分钟
Mishmash10分钟
Practical R Exercises in swirl Part 410分钟
Post-Course Survey10分钟
Quiz1 个练习
Quiz 412分钟
4.4
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22%

完成这些课程后已开始新的职业生涯
Briefcase

83%

通过此课程获得实实在在的工作福利
Money

14%

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热门审阅

创建者 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.

创建者 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.

讲师

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

关于 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....

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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....
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