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.
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教学大纲 - 您将从这门课程中学到什么
周
1完成时间为 12 分钟
About Introduction to Probability and Data
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.
1 个视频 （总计 2 分钟）, 1 个阅读材料
1 个阅读材料
More about Introduction to Probability and Data10分钟
完成时间为 1 小时
Introduction to Data
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.
6 个视频 （总计 28 分钟）, 2 个阅读材料, 2 个测验
6 个视频
Introduction3分钟
Data Basics5分钟
Observational Studies & Experiments4分钟
Sampling and sources of bias8分钟
Experimental Design2分钟
(Spotlight) Random Sample Assignment3分钟
2 个阅读材料
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
2 个练习
Week 1 Practice Quiz10分钟
Week 1 Quiz14分钟
完成时间为 1 小时
Introduction to Data Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
2 个阅读材料, 1 个测验
2 个阅读材料
About Lab Choices (Read Before Selection)10分钟
Week 1 Lab Instructions (RStudio)10分钟
1 个练习
Week 1 Lab: Introduction to R and RStudio16分钟
周
2完成时间为 2 小时
Exploratory Data Analysis and Introduction to Inference
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.
7 个视频 （总计 46 分钟）, 3 个阅读材料, 2 个测验
7 个视频
Measures of Center4分钟
Measures of Spread6分钟
Robust Statistics1分钟
Transforming Data3分钟
Exploring Categorical Variables8分钟
Introduction to Inference12分钟
3 个阅读材料
Lesson Learning Objectives10分钟
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
2 个练习
Week 2 Practice Quiz10分钟
Week 2 Quiz12分钟
完成时间为 1 小时
Exploratory Data Analysis and Introduction to Inference Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
2 个阅读材料, 1 个测验
2 个阅读材料
Week 2 Lab Instructions (RStudio)10分钟
Week 2 Lab Instructions (RStudio Cloud)10分钟
1 个练习
Week 2 Lab: Introduction to Data20分钟
周
3完成时间为 2 小时
Introduction to Probability
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.
9 个视频 （总计 82 分钟）, 3 个阅读材料, 2 个测验
9 个视频
Introduction5分钟
Disjoint Events + General Addition Rule9分钟
Independence9分钟
Probability Examples9分钟
(Spotlight) Disjoint vs. Independent2分钟
Conditional Probability12分钟
Probability Trees10分钟
Bayesian Inference14分钟
Examples of Bayesian Inference7分钟
3 个阅读材料
Lesson Learning Objectives10分钟
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
2 个练习
Week 3 Practice Quiz6分钟
Week 3 Quiz10分钟
完成时间为 1 小时
Introduction to Probability Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
2 个阅读材料, 1 个测验
2 个阅读材料
Week 3 Lab Instructions (RStudio)10分钟
Week 3 Lab Instructions (RStudio Cloud)10分钟
1 个练习
Week 3 Lab: Probability10分钟
周
4完成时间为 2 小时
Probability Distributions
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).
6 个视频 （总计 67 分钟）, 4 个阅读材料, 2 个测验
6 个视频
Evaluating the Normal Distribution2分钟
Working with the Normal Distribution5分钟
Binomial Distribution17分钟
Normal Approximation to Binomial14分钟
Working with the Binomial Distribution9分钟
4 个阅读材料
Lesson Learning Objectives10分钟
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
Data Analysis Project Example10分钟
2 个练习
Week 4 Practice Quiz14分钟
Week 4 Quiz14分钟
4.7
755 个审阅33%
完成这些课程后已开始新的职业生涯
30%
通过此课程获得实实在在的工作福利
11%
加薪或升职
来自Introduction to Probability and Data的热门评论
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.
Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.
讲师
Mine Çetinkaya-Rundel
Associate Professor of the PracticeDepartment of Statistical Science
关于 杜克大学
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.
关于 Statistics with R 专项课程
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.
常见问题
我什么时候能够访问课程视频和作业？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
退款政策是如何规定的？
有助学金吗？
Will I receive a transcript from Duke University for completing this course?
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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