About this Course

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Learner Career Outcomes

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Shareable Certificate
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Approx. 54 hours to complete
English

What you will learn

  • Use regression analysis, least squares and inference

  • Understand ANOVA and ANCOVA model cases

  • Investigate analysis of residuals and variability

  • Describe novel uses of regression models such as scatterplot smoothing

Skills you will gain

Model SelectionGeneralized Linear ModelLinear RegressionRegression Analysis

Learner Career Outcomes

23%

started a new career after completing these courses

25%

got a tangible career benefit from this course

14%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 54 hours to complete
English

Offered by

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Johns Hopkins University

Syllabus - What you will learn from this course

Content RatingThumbs Up92%(10,379 ratings)Info
Week
1

Week 1

13 hours to complete

Week 1: Least Squares and Linear Regression

13 hours to complete
9 videos (Total 74 min), 11 readings, 4 quizzes
9 videos
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 readings
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 practice exercise
Quiz 130m
Week
2

Week 2

11 hours to complete

Week 2: Linear Regression & Multivariable Regression

11 hours to complete
10 videos (Total 70 min), 5 readings, 4 quizzes
10 videos
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 readings
*Statistical* linear regression models10m
Residuals10m
Inference in regression10m
Looking ahead to the project10m
Practical R Exercises in swirl Part 210m
1 practice exercise
Quiz 230m
Week
3

Week 3

14 hours to complete

Week 3: Multivariable Regression, Residuals, & Diagnostics

14 hours to complete
14 videos (Total 168 min), 5 readings, 5 quizzes
14 videos
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 readings
Multivariable regression10m
Adjustment10m
Residuals10m
Model selection10m
Practical R Exercises in swirl Part 310m
2 practice exercises
Quiz 330m
(OPTIONAL) Data analysis practice with immediate feedback (NEW! 10/18/2017)30m
Week
4

Week 4

16 hours to complete

Week 4: Logistic Regression and Poisson Regression

16 hours to complete
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 readings
GLMs10m
Logistic regression10m
Count Data10m
Mishmash10m
Practical R Exercises in swirl Part 410m
Post-Course Survey10m
1 practice exercise
Quiz 430m

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