About this Course

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Learner Career Outcomes

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started a new career after completing these courses

30%

got a tangible career benefit from this course

11%

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. 11 hours to complete
English
Subtitles: English, Korean

Skills you will gain

StatisticsR ProgrammingRstudioExploratory Data Analysis

Learner Career Outcomes

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
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. 11 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%(23,332 ratings)Info
Week
1

Week 1

12 minutes to complete

About Introduction to Probability and Data

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

Introduction to Data

1 hour to complete
6 videos (Total 28 min), 2 readings, 2 quizzes
6 videos
Data Basics5m
Observational Studies & Experiments4m
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

1 hour to complete
2 readings
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

Week 2

2 hours to complete

Exploratory Data Analysis and Introduction to Inference

2 hours to complete
7 videos (Total 46 min), 3 readings, 2 quizzes
7 videos
Measures of Center4m
Measures of Spread6m
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

1 hour to complete
2 readings
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

Week 3

2 hours to complete

Introduction to Probability

2 hours to complete
9 videos (Total 82 min), 3 readings, 2 quizzes
9 videos
Disjoint Events + General Addition Rule9m
Independence9m
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

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

Week 4

2 hours to complete

Probability Distributions

2 hours to complete
6 videos (Total 67 min), 4 readings, 2 quizzes
6 videos
Evaluating the Normal Distribution2m
Working with the Normal Distribution5m
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

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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

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    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • 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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