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Introduction to Probability and Data

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HomeData ScienceData Analysis

Introduction to Probability and Data

Duke University

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
Duke University

  • Mine Çetinkaya-Rundel

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

    Department of Statistical Science
Basic Info
Course 1 of 5 in the Statistics with R Specialization
LevelBeginner
Commitment5 weeks of study, 5-7 hours/week
Language
English, Subtitles: Korean
How To PassPass all graded assignments to complete the course.
User Ratings
4.7 stars
Average User Rating 4.7See what learners said
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
  1. Video: Introduction to Statistics with R
  2. Leitura: More about Introduction to Probability and Data
  3. Leitura: 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
  1. Leitura: 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. Leitura: Suggested Readings and Practice
  9. Teste para praticar: Week 1 Practice Quiz
  10. Leitura: About Lesson Choices (Read Before Selection)
  11. Leitura: Week 1 Lab Instructions (RStudio)
  12. Leitura: 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
  1. Leitura: 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. Leitura: Lesson Learning Objectives
  8. Video: Exploring Categorical Variables
  9. Video: Introduction to Inference
  10. Leitura: Suggested Readings and Practice
  11. Teste para praticar: Week 2 Practice Quiz
  12. Leitura: Week 2 Lab Instructions (RStudio)
  13. Leitura: 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
  1. Leitura: 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. Leitura: Lesson Learning Objectives
  8. Video: Conditional Probability
  9. Video: Probability Trees
  10. Video: Bayesian Inference
  11. Video: Examples of Bayesian Inference
  12. Leitura: Suggested Readings and Practice
  13. Teste para praticar: Week 3 Practice Quiz
  14. Leitura: Week 3 Lab Instructions (RStudio)
  15. Leitura: 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
  1. Leitura: Lesson Learning Objectives
  2. Video: Normal Distribution
  3. Video: Evaluating the Normal Distribution
  4. Video: Working with the Normal Distribution
  5. Leitura: Lesson Learning Objectives
  6. Video: Binomial Distribution
  7. Video: Normal Approximation to Binomial
  8. Video: Working with the Binomial Distribution
  9. Leitura: Suggested Readings and Practice
  10. Teste para praticar: Week 4 Practice Quiz
  11. Leitura: Feedback survey
  12. Leitura: 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
  1. Leitura: Project Information
  2. Leitura: Feedback survey
Graded: Data Analysis Project

FAQs
How It Works
Trabalho
Trabalho

Cada curso é como um livro didático interativo, com vídeos pré-gravados, testes e projetos.

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Conecte-se com milhares de outros aprendizes, debata ideias, discuta sobre os materiais do curso e obtenha ajuda para dominar conceitos.

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Obtenha reconhecimento oficial pelo seu trabalho e compartilhe seu sucesso com amigos, colegas e empregadores.

Creators
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.
Pricing
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Ratings and Reviews
Rated 4.7 out of 5 of 2,057 ratings
Le Quy Duong

A good beginning of statistics and R, I like the way the assignment is organized.

Lm

Helpful !! learnt solving problems with probability perspective .. which is will give more confidence while solving real time analytical problems

SS

very good for beginners

YL

Useful course! very clear to make points. The instructor is very good at teaching. recommend. One thing I don't like is that for the peer review project, you have wait to long before some one else review your work and get the certificate.



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