About this Course

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Learner Career Outcomes

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started a new career after completing these courses

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got a tangible career benefit from this course

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Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 25 hours to complete

Suggested: 5 weeks of study, 5-7 hours/week...

English

Subtitles: English, Korean

Skills you will gain

Statistical InferenceStatistical Hypothesis TestingR Programming

Learner Career Outcomes

33%

started a new career after completing these courses

22%

got a tangible career benefit from this course

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 25 hours to complete

Suggested: 5 weeks of study, 5-7 hours/week...

English

Subtitles: English, Korean

Offered by

Duke University logo

Duke University

Syllabus - What you will learn from this course

Content RatingThumbs Up93%(5,603 ratings)Info
Week
1

Week 1

20 minutes to complete

About the Specialization and the Course

20 minutes to complete
2 readings
2 readings
About Statistics with R Specialization10m
More about Inferential Statistics10m
3 hours to complete

Central Limit Theorem and Confidence Interval

3 hours to complete
7 videos (Total 65 min), 6 readings, 3 quizzes
7 videos
Sampling Variability and CLT20m
CLT (for the mean) examples10m
Confidence Interval (for a mean)11m
Accuracy vs. Precision7m
Required Sample Size for ME4m
CI (for the mean) examples5m
6 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 1 Suggested Readings and Practice Exercises10m
About Lab Choices10m
Week 1 Lab Instructions (RStudio)10m
Week 1 Lab Instructions (RStudio Cloud)10m
3 practice exercises
Week 1 Practice Quiz12m
Week 1 Quiz14m
Week 1 Lab12m
Week
2

Week 2

2 hours to complete

Inference and Significance

2 hours to complete
7 videos (Total 59 min), 5 readings, 3 quizzes
7 videos
Hypothesis Testing (for a mean)14m
HT (for the mean) examples9m
Inference for Other Estimators10m
Decision Errors8m
Significance vs. Confidence Level6m
Statistical vs. Practical Significance7m
5 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 2 Suggested Readings and Practice Exercises10m
Week 2 Lab Instructions (RStudio)10m
Week 2 Lab Instructions (RStudio Cloud)10m
3 practice exercises
Week 2 Practice Quiz10m
Week 2 Quiz16m
Week 2 Lab12m
Week
3

Week 3

3 hours to complete

Inference for Comparing Means

3 hours to complete
11 videos (Total 84 min), 5 readings, 3 quizzes
11 videos
t-distribution7m
Inference for a mean9m
Inference for comparing two independent means8m
Inference for comparing two paired means9m
Power11m
Comparing more than two means6m
ANOVA9m
Conditions for ANOVA2m
Multiple comparisons6m
Bootstrapping8m
5 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 3 Suggested Readings and Practice Exercises10m
Week 3 Lab Instructions (RStudio)10m
Week 3 Lab Instructions (RStudio Cloud)10m
3 practice exercises
Week 3 Practice Quiz16m
Week 3 Quiz28m
Week 3 Lab14m
Week
4

Week 4

4 hours to complete

Inference for Proportions

4 hours to complete
11 videos (Total 118 min), 5 readings, 3 quizzes
11 videos
Sampling Variability and CLT for Proportions15m
Confidence Interval for a Proportion9m
Hypothesis Test for a Proportion9m
Estimating the Difference Between Two Proportions17m
Hypothesis Test for Comparing Two Proportions13m
Small Sample Proportions10m
Examples4m
Comparing Two Small Sample Proportions5m
Chi-Square GOF Test14m
The Chi-Square Independence Test11m
5 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 4 Suggested Readings and Practice Exercises10m
Week 4 Lab Instructions (RStudio)10m
Week 4 Lab Instructions (RStudio Cloud)10m
3 practice exercises
Week 4 Practice Quiz18m
Week 4 Quiz24m
Week 4 Lab26m
4.8
289 ReviewsChevron Right

Top reviews from Inferential Statistics

By MNMar 1st 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

By ZCAug 24th 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

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 want to complete the course and earn a Course Certificate by submitting assignments for a grade, you can upgrade your experience by subscribing to the course for $49/month. You can also apply for financial aid if you can't afford the course fee.

    When you enroll in a course that is part of a Specialization (which this course is), you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses or cancel your subscription once you complete the single course.

  • To enroll in an individual course, search for the course title in the catalog.

    To get full access to a course, including the option to earn grades and a Course Certificate, you'll need to subscribe. New subscribers will start with a full access subscription, which includes full access to every course in the Coursera catalog. Existing Specialization subscribers will be given the option to update to a full access subscription when enrolling in a new Specialization or course.

    When you enroll in a course that is part of a Specialization, you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses.

  • 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.