4.4
2,505 個評分
432 個審閱

### 您將學到的內容有

• 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

### 您將獲得的技能

Model SelectionGeneralized Linear ModelLinear RegressionRegression Analysis

1

## Week 1: Least Squares and Linear Regression

This week, we focus on least squares and linear regression....
9 個視頻 （總計 74 分鐘）, 11 個閱讀材料, 4 個測驗
9 個視頻
Introduction: Basic Least Squares6分鐘
Technical Details (Skip if you'd like)2分鐘
Introductory Data Example12分鐘
Notation and Background7分鐘
Linear Least Squares6分鐘
Linear Least Squares Coding Example7分鐘
Technical Details (Skip if you'd like)11分鐘
Regression to the Mean11分鐘
11 個閱讀材料
Welcome to Regression Models10分鐘
Book: Regression Models for Data Science in R10分鐘
Syllabus10分鐘
Pre-Course Survey10分鐘
Data Science Specialization Community Site10分鐘
Where to get more advanced material10分鐘
Regression10分鐘
Technical details10分鐘
Least squares10分鐘
Regression to the mean10分鐘
Practical R Exercises in swirl Part 110分鐘
1 個練習
Quiz 120分鐘
2

## 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 個視頻 （總計 70 分鐘）, 5 個閱讀材料, 4 個測驗
10 個視頻
Interpreting Coefficients3分鐘
Linear Regression for Prediction10分鐘
Residuals5分鐘
Residuals, Coding Example14分鐘
Residual Variance7分鐘
Inference in Regression5分鐘
Coding Example6分鐘
Prediction9分鐘
Really, really quick intro to knitr3分鐘
5 個閱讀材料
*Statistical* linear regression models10分鐘
Residuals10分鐘
Inference in regression10分鐘
Practical R Exercises in swirl Part 210分鐘
1 個練習
Quiz 220分鐘
3

## 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 個視頻 （總計 168 分鐘）, 5 個閱讀材料, 5 個測驗
14 個視頻
Multivariable Regression part II10分鐘
Multivariable Regression Continued8分鐘
Multivariable Regression Examples part I19分鐘
Multivariable Regression Examples part II22分鐘
Multivariable Regression Examples part III7分鐘
Multivariable Regression Examples part IV7分鐘
Residuals and Diagnostics part I5分鐘
Residuals and Diagnostics part II9分鐘
Residuals and Diagnostics part III9分鐘
Model Selection part I7分鐘
Model Selection part II22分鐘
Model Selection part III12分鐘
5 個閱讀材料
Multivariable regression10分鐘
Residuals10分鐘
Model selection10分鐘
Practical R Exercises in swirl Part 310分鐘
2 個練習
Quiz 314分鐘
(OPTIONAL) Data analysis practice with immediate feedback (NEW! 10/18/2017)8分鐘
4

## Week 4: Logistic Regression and Poisson Regression

This week, we will work on generalized linear models, including binary outcomes and Poisson regression. ...
7 個視頻 （總計 95 分鐘）, 6 個閱讀材料, 6 個測驗
7 個視頻
GLMs21分鐘
Logistic Regression part I17分鐘
Logistic Regression part II3分鐘
Logistic Regression part III8分鐘
Poisson Regression part I12分鐘
Poisson Regression part II12分鐘
Hodgepodge18分鐘
6 個閱讀材料
GLMs10分鐘
Logistic regression10分鐘
Count Data10分鐘
Mishmash10分鐘
Practical R Exercises in swirl Part 410分鐘
Post-Course Survey10分鐘
1 個練習
Quiz 412分鐘
4.4
432 個審閱

## 12%

### 熱門審閱

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.

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.

## 講師

### 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

## 關於 约翰霍普金斯大学

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....

## 關於 数据科学 專項課程

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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