Duke University
Introduction to Probability and Data with R
Duke University

Introduction to Probability and Data with R

Sponsored by Duke Alumni

288,633 already enrolled

Gain insight into a topic and learn the fundamentals.
4.7

(5,663 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 14 hours
Learn at your own pace
94%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.7

(5,663 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 14 hours
Learn at your own pace
94%
Most learners liked this course

Details to know

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Assessments

11 assignments

Taught in English

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This course is part of the Data Analysis with R Specialization
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There are 8 modules in this course

This course introduces you to sampling and exploring data, as well as basic probability theory. You will examine various types of sampling methods and discuss how such methods can impact the utility of a data analysis. The concepts in this module will serve as building blocks for our later courses.Each lesson comes with a set of learning objectives that will be covered in a series of short videos. Supplementary readings and practice problems will also be suggested from OpenIntro Statistics, 3rd Edition, https://leanpub.com/openintro-statistics/, (a free online introductory statistics textbook, that I co-authored). There will be weekly quizzes designed to assess your learning and mastery of the material covered that week in the videos. In addition, each week will also feature a lab assignment, in which you will use R to apply what you are learning to real data. There will also be a data analysis project designed to enable you to answer research questions of your own choosing. Since this is a Coursera course, you are welcome to participate as much or as little as you’d like, though I hope that you will begin by participating fully. One of the most rewarding aspects of a Coursera course is participation in forum discussions about the course materials. Please take advantage of other students' feedback and insight and contribute your own perspective where you see fit to do so. You can also check out the resource page (https://www.coursera.org/learn/probability-intro/resources/crMc4) listing useful resources for this course. Thank you for joining the Introduction to Probability and Data community! Say hello in the Discussion Forums. We are looking forward to your participation in the course.

What's included

1 video1 reading

Welcome to Introduction to Probability and Data! I hope you are just as excited about this course as I am! In the next five weeks, we will learn about designing studies, explore data via numerical summaries and visualizations, and learn about rules of probability and commonly used probability distributions. If you have any questions, feel free to post them on this module's forum (https://www.coursera.org/learn/probability-intro/module/rQ9Al/discussions?sort=lastActivityAtDesc&page=1) and discuss with your peers! To get started, view the learning objectives (https://www.coursera.org/learn/probability-intro/supplement/rooeY/lesson-learning-objectives) of Lesson 1 in this module.

What's included

6 videos2 readings2 assignments

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.

What's included

2 readings1 assignment

Welcome to Week 2 of Introduction to Probability and Data! Hope you enjoyed materials from Week 1. This week we will delve into numerical and categorical data in more depth, and introduce inference.

What's included

7 videos3 readings2 assignments

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.

What's included

2 readings1 assignment

Welcome to Week 3 of Introduction to Probability and Data! Last week we explored numerical and categorical data. This week we will discuss probability, conditional probability, the Bayes’ theorem, and provide a light introduction to Bayesian inference. Thank you for your enthusiasm and participation, and have a great week! I’m looking forward to working with you on the rest of this course.

What's included

9 videos3 readings2 assignments

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.

What's included

2 readings1 assignment

Great work so far! Welcome to Week 4 -- the last content week of Introduction to Probability and Data! This week we will introduce two probability distributions: the normal and the binomial distributions in particular. As usual, you can evaluate your knowledge in this week's quiz. There will be no labs for this week. Please don't hesitate to post any questions, discussions and related topics on this week's forum (https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1). Also this week, you will be asked to complete an initial data analysis project with a real-world data set. The project is designed to help you discover and explore research questions of your own, using real data and statistical methods we learn in this class. Please read the project instructions to complete this self-assessment.

What's included

6 videos4 readings2 assignments

Instructor

Instructor ratings
4.8 (752 ratings)
Mine Çetinkaya-Rundel
Duke University
9 Courses398,331 learners

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Duke University

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