About this Course

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Learner Career Outcomes

33%

started a new career after completing these courses

45%

got a tangible career benefit from this course

12%

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.

Beginner Level

Approx. 9 hours to complete

English

Subtitles: English, Korean

Skills you will gain

StatisticsLinear RegressionR ProgrammingRegression Analysis

Learner Career Outcomes

33%

started a new career after completing these courses

45%

got a tangible career benefit from this course

12%

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.

Beginner Level

Approx. 9 hours to complete

English

Subtitles: English, Korean

Offered by

Duke University logo

Duke University

Syllabus - What you will learn from this course

Content RatingThumbs Up94%(3,141 ratings)Info
Week
1

Week 1

22 minutes to complete

About Linear Regression and Modeling

22 minutes to complete
1 video (Total 2 min), 2 readings
2 readings
About Statistics with R Specialization10m
More about Linear Regression and Modeling10m
2 hours to complete

Linear Regression

2 hours to complete
8 videos (Total 47 min), 3 readings, 2 quizzes
8 videos
Correlation9m
Residuals1m
Least Squares Line11m
Prediction and Extrapolation3m
Conditions for Linear Regression10m
R Squared4m
Regression with Categorical Explanatory Variables5m
3 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 1 Suggested Readings and Practice10m
2 practice exercises
Week 1 Practice Quiz8m
Week 1 Quiz18m
Week
2

Week 2

2 hours to complete

More about Linear Regression

2 hours to complete
3 videos (Total 24 min), 5 readings, 3 quizzes
3 videos
Inference for Linear Regression11m
Variability Partitioning5m
5 readings
Lesson Learning Objectives10m
Week 2 Suggested Readings and Exercises10m
About Lab Choices10m
Week 1 & 2 Lab Instructions (RStudio)10m
Week 1 & 2 Lab Instructions (RStudio Cloud)10m
3 practice exercises
Week 2 Practice Quiz6m
Week 2 Quiz16m
Week 1 & 2 Lab20m
Week
3

Week 3

3 hours to complete

Multiple Regression

3 hours to complete
7 videos (Total 57 min), 5 readings, 3 quizzes
7 videos
Multiple Predictors11m
Adjusted R Squared10m
Collinearity and Parsimony3m
Inference for MLR11m
Model Selection11m
Diagnostics for MLR7m
5 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 3 Suggested Readings and Exercises10m
Week 3 Lab Instructions (RStudio)10m
Week 3 Lab Instructions (RStudio Cloud)10m
3 practice exercises
Week 3 Practice Quiz16m
Week 3 Quiz20m
Week 3 Lab20m
Week
4

Week 4

2 hours to complete

Final Project

2 hours to complete
1 reading
1 reading
Project Files and Rubric10m

About the Statistics with R Specialization

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions....
Statistics with R

Frequently Asked Questions

  • 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.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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