Created by:  Duke University

  • Merlise A Clyde

    Taught by:  Merlise A Clyde, Professor

    Department of Statistical Science

  • Colin Rundel

    Taught by:  Colin Rundel , Assistant Professor of the Practice

    Statistical Science

  • David Banks

    Taught by:  David Banks, Professor of the Practice

    Statistical Science

  • Mine Çetinkaya-Rundel

    Taught by:  Mine Çetinkaya-Rundel, Assistant Professor of the Practice

    Department of Statistical Science
Basic Info
Course 5 of 5 in the Statistics with R Specialization.
Commitment5-10 hours/week
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.7 stars
Average User Rating 4.7See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators
Duke University
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Pricing
AuditPurchase Course
Access to course materials

Available

Available

Access to graded materials

Not available

Available

Receive a final grade

Not available

Available

Earn a shareable Course Certificate

Not available

Available

Ratings and Reviews
Rated 4.7 out of 5 of 17 ratings

Thank you very much for teaching me all the statistics courses in the specialization. Although it is an online study, I think I benefit a lot from the course contents, quizzes and problem sets and the training from final projects one by one. Also, I appreciate a lot the feedback from other students in the courses, which gives me more confidence on my study. As a matter of fact, I know I still have a lot of room to improve on my final project, such as consistency of EDA with the later part of my project, assessment on residual plots, real understanding on the trade off between model interpretation and prediction accuracy, etc., which I will improve in my future study and analysis. No matter where and what I will study in the future, I always bring the statistics knowledge and R skills that I learned from my first specialization from professors at Duke University. Thank you.

The Capstone project really helped tie the program together

I think this is a very advisable course as a whole, The capstone offers a good occasion to put into practice what has been learned during the four previous courses and also works as a sort of review.

Great activity!!