Introduction to Probability and Data

About this course: This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.

Created by:  Duke University

• Taught by:  Mine Çetinkaya-Rundel, Assistant Professor of the Practice

  Department of Statistical Science

Basic Info Course 1 of 5 in the Statistics with R Specialization Level Beginner Commitment 5 weeks of study, 5-7 hours/week Language English, Subtitles: Korean How To Pass Pass all graded assignments to complete the course. User Ratings 4.7 stars Average User Rating 4.7See what learners said Coursework

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Syllabus


WEEK 1


About Introduction to Probability and Data



<p>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.<p>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 <a href="https://leanpub.com/openintro-statistics/" target="_blank">OpenIntro Statistics, 3rd Edition</a> (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.<p>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 <a href="https://www.coursera.org/learn/probability-intro/resources/crMc4" target="_blank">resource page</a> listing useful resources for this course. <p>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.</p>


1 video, 2 readings expand

1. Video: Introduction to Statistics with R
2. Reading: about Introduction to Probability and Data
3. Reading: Feedback Surveys

Introduction to Data



<p>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 <a href="https://www.coursera.org/learn/probability-intro/module/rQ9Al/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this module's forum</b></a> and discuss with your peers! To get started, view the <a href="https://www.coursera.org/learn/probability-intro/supplement/rooeY/lesson-learning-objectives" target="_blank"><b>learning objectives</b></a> of Lesson 1 in this module.</p>


6 videos, 5 readings, 1 practice quiz expand

1. Reading: Lesson Learning Objectives
2. Video: Introduction
3. Video: Data Basics
4. Video: Observational Studies & Experiments
5. Video: Sampling and sources of bias
6. Video: Experimental Design
7. Video: (Spotlight) Random Sample Assignment
8. Reading: Suggested Readings and Practice
9. Practice Quiz: Week 1 Practice Quiz
10. Reading: About Lesson Choices (Read Before Selection)
11. Reading: Week 1 Lab Instructions (RStudio)
12. Reading: Feedback survey

Graded: Week 1 Quiz
Graded: Week 1 Lab: Introduction to R and RStudio

WEEK 2


Exploratory Data Analysis and Introduction to Inference
<p>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. </p>


7 videos, 5 readings, 1 practice quiz expand

1. Reading: Lesson Learning Objectives
2. Video: Visualizing Numerical Data
3. Video: Measures of Center
4. Video: Measures of Spread
5. Video: Robust Statistics
6. Video: Transforming Data
7. Reading: Lesson Learning Objectives
8. Video: Exploring Categorical Variables
9. Video: Introduction to Inference
10. Reading: Suggested Readings and Practice
11. Practice Quiz: Week 2 Practice Quiz
12. Reading: Week 2 Lab Instructions (RStudio)
13. Reading: Feedback survey

Graded: Week 2 Quiz
Graded: Week 2 Lab: Introduction to Data

WEEK 3


Introduction to Probability



<p>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. </p><p>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. </p>


9 videos, 5 readings, 1 practice quiz expand

1. Reading: Lesson Learning Objectives
2. Video: Introduction
3. Video: Disjoint Events + General Addition Rule
4. Video: Independence
5. Video: Probability Examples
6. Video: (Spotlight) Disjoint vs. Independent
7. Reading: Lesson Learning Objectives
8. Video: Conditional Probability
9. Video: Probability Trees
10. Video: Bayesian Inference
11. Video: Examples of Bayesian Inference
12. Reading: Suggested Readings and Practice
13. Practice Quiz: Week 3 Practice Quiz
14. Reading: Week 3 Lab Instructions (RStudio)
15. Reading: Feedback survey

Graded: Week 3 Quiz
Graded: Week 3 Lab: Probability

WEEK 4


Probability Distributions



<p>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 <b>no labs</b> for this week. Please don't hesitate to post any questions, discussions and related topics on <a href="https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this week's forum</b></a>.</p>


6 videos, 5 readings, 1 practice quiz expand

1. Reading: Lesson Learning Objectives
2. Video: Normal Distribution
3. Video: Evaluating the Normal Distribution
4. Video: Working with the Normal Distribution
5. Reading: Lesson Learning Objectives
6. Video: Binomial Distribution
7. Video: Normal Approximation to Binomial
8. Video: Working with the Binomial Distribution
9. Reading: Suggested Readings and Practice
10. Practice Quiz: Week 4 Practice Quiz
11. Reading: Feedback survey
12. Reading: Data Analysis Project Example

Graded: Week 4 Quiz

WEEK 5


Data Analysis Project



<p>Well done! You have reached the last week of Introduction to Probability and Data! There will not be any new videos in this week, instead, 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. The the project will be graded via peer assessments, meaning that you will need to evaluate three peers' projects after submitting your own.</p><p>Get started with your data analysis in this week! It should be interesting and very exciting! As usual, feel free to post questions, concerns, and comments about the project on <a href="https://www.coursera.org/learn/probability-intro/module/BaTDb/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this week's forum</b></a>.</p>


2 readings expand

1. Reading: Project Information
2. Reading: Feedback survey

Graded: Data Analysis Project