About this Course
214,495 recent views

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 22 hours to complete

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

English

Subtitles: English, Korean

Skills you will gain

StatisticsR ProgrammingRstudioExploratory Data Analysis

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 22 hours to complete

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

English

Subtitles: English, Korean

Syllabus - What you will learn from this course

Week
1
12 minutes to complete

About Introduction to Probability and Data

1 video (Total 2 min), 1 reading
1 reading
More about Introduction to Probability and Data10m
1 hour to complete

Introduction to Data

6 videos (Total 28 min), 2 readings, 2 quizzes
6 videos
Sampling and sources of bias8m
Experimental Design2m
(Spotlight) Random Sample Assignment3m
2 readings
Lesson Learning Objectives10m
Suggested Readings and Practice10m
2 practice exercises
Week 1 Practice Quiz10m
Week 1 Quiz14m
1 hour to complete

Introduction to Data Project

2 readings, 1 quiz
2 readings
About Lab Choices (Read Before Selection)10m
Week 1 Lab Instructions (RStudio)10m
1 practice exercise
Week 1 Lab: Introduction to R and RStudio16m
Week
2
2 hours to complete

Exploratory Data Analysis and Introduction to Inference

7 videos (Total 46 min), 3 readings, 2 quizzes
7 videos
Robust Statistics1m
Transforming Data3m
Exploring Categorical Variables8m
Introduction to Inference12m
3 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Suggested Readings and Practice10m
2 practice exercises
Week 2 Practice Quiz10m
Week 2 Quiz12m
1 hour to complete

Exploratory Data Analysis and Introduction to Inference Project

2 readings, 1 quiz
2 readings
Week 2 Lab Instructions (RStudio)10m
Week 2 Lab Instructions (RStudio Cloud)10m
1 practice exercise
Week 2 Lab: Introduction to Data20m
Week
3
2 hours to complete

Introduction to Probability

9 videos (Total 82 min), 3 readings, 2 quizzes
9 videos
Probability Examples9m
(Spotlight) Disjoint vs. Independent2m
Conditional Probability12m
Probability Trees10m
Bayesian Inference14m
Examples of Bayesian Inference7m
3 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Suggested Readings and Practice10m
2 practice exercises
Week 3 Practice Quiz6m
Week 3 Quiz10m
1 hour to complete

Introduction to Probability Project

2 readings, 1 quiz
2 readings
Week 3 Lab Instructions (RStudio)10m
Week 3 Lab Instructions (RStudio Cloud)10m
1 practice exercise
Week 3 Lab: Probability10m
Week
4
2 hours to complete

Probability Distributions

6 videos (Total 67 min), 4 readings, 2 quizzes
6 videos
Binomial Distribution17m
Normal Approximation to Binomial14m
Working with the Binomial Distribution9m
4 readings
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Suggested Readings and Practice10m
Data Analysis Project Example10m
2 practice exercises
Week 4 Practice Quiz14m
Week 4 Quiz14m
4.7
702 ReviewsChevron Right

33%

started a new career after completing these courses

30%

got a tangible career benefit from this course

11%

got a pay increase or promotion

Top reviews from Introduction to Probability and Data

By AAJan 24th 2018

This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.

By HDMar 31st 2018

The tutor makes it really simple. The given examples really helped to understand the concepts and apply it to a wide range of problems. Thank you for this. Wish I could complete the assignments too.

Instructor

Avatar

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.