About this Course
4.7
92 ratings
24 reviews
Specialization
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100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 10 hours to complete

Suggested: 5-10 hours/week...
Available languages

English

Subtitles: English...

Skills you will gain

Model SelectionBayesian StatisticsStatistical AnalysisR Programming
Specialization
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 10 hours to complete

Suggested: 5-10 hours/week...
Available languages

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Hours to complete
1 hour to complete

About the Capstone Project

Welcome to the capstone project! This week's content is an introduction to the project assignment and goals. The readings in this week will introduce the data set that you will be analyzing for your project and the specific questions you will answer using data analysis techniques we learned in the previous courses. It is important to understand what we will be doing in the course before jumping into the detailed analysis. So we encourage you to start with the first lecture to get the big picture, and then delve into the specifics of the analysis. Enjoy, and good luck! Remember, if you have questions, you can post them on the discussion forums....
Reading
1 video (Total 6 min), 4 readings
Reading4 readings
Introduction to the Capstone Course10m
Tips for Success and Suggested Work Pace10m
What to Do This Week5m
Learning Objectives for Courses 1-410m
Week
2
Hours to complete
1 hour to complete

Exploratory Data Analysis (EDA)

This week you will work on conducting an exploratory analysis of the housing data. Exploratory analysis is an essential first step for familiarizing yourself with and understanding the data. In this week, you will complete a quiz which will guide you through certain important aspects of the data. The insights you gain through this assignment will help inform modeling in the future quizzes and peer assessments. Feel free to post questions about this assignment on the discussion forum. ...
Reading
2 readings, 1 quiz
Reading2 readings
What to Do This Week10m
EDA Quiz - Assignment Guide10m
Quiz1 practice exercise
EDA Quiz28m
Week
3
Hours to complete
5 minutes to complete

EDA and Basic Model Selection - Submission

This week we will dig deeper into our exploratory data analysis of the data. We now have all the information and data necessary to perform a deep dive into the EDA and it is time start your initial analysis report! We encourage you to start your analysis report (presented in peer-review format next week) early so you will have enough time to complete it. You will conduct exploratory data analysis, model selection, and model evaluation, and then complete a written report which answers several questions which will guide you through the process. This report will be your first peer-review assignment in this course. ...
Reading
1 reading
Reading1 reading
What to Do This Week5m
Week
4
Hours to complete
2 hours to complete

EDA and Basic Model Selection - Evaluation

Great work so far! We hope you will also learn as much from evaluating your peers' work as completing your own assignment. Happy learning!...
Reading
1 reading, 1 quiz
Reading1 reading
What to Do This Week10m
4.7
Career direction

50%

started a new career after completing these courses
Career Benefit

83%

got a tangible career benefit from this course

Top Reviews

By JNMar 24th 2017

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.

By ACJul 13th 2017

Great course, learned a lot and got me started on another project that I've turned into a really nice portfolio item. I feel much more comfortable with R and statistics principles.

Instructors

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Merlise A Clyde

Professor
Department of Statistical Science
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Colin Rundel

Assistant Professor of the Practice
Statistical Science
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David Banks

Professor of the Practice
Statistical Science
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Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

About 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....

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.

  • 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.

More questions? Visit the Learner Help Center.