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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课程信息
567,165 次近期查看
学生职业成果
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
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 1 门课程（共 5 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为11 小时
英语（English）
字幕：英语（English）, 韩语
您将获得的技能
StatisticsR ProgrammingRstudioExploratory Data Analysis
学生职业成果
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
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 1 门课程（共 5 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为11 小时
英语（English）
字幕：英语（English）, 韩语
提供方
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.
教学大纲 - 您将从这门课程中学到什么
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.
完成时间为 12 分钟
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.
完成时间为 1 小时
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.
完成时间为 1 小时
2 个阅读材料
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
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.
完成时间为 2 小时
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.
完成时间为 1 小时
2 个阅读材料
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
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.
完成时间为 2 小时
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.
完成时间为 1 小时
2 个阅读材料
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
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).
完成时间为 2 小时
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
审阅
来自INTRODUCTION TO PROBABILITY AND DATA WITH R的热门评论
由 AA 提供Jan 23, 2018
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.
由 HD 提供Mar 30, 2018
The tutor makes it really simple. The given examples really helped to understand the concepts and apply it to a wide range of problems. Thank you for this. Wish I could complete the assignments too.
由 AA 提供Jun 9, 2017
A good introductory course to data analysis, statistics and the R programming language. Recommended to people who are new to data analysis and also those who are experienced and could use a refresh.
由 BB 提供Sep 3, 2019
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.
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？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
- 课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
- 课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
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？
如果订阅，您可以获得 7 天免费试听，在此期间，您可以取消课程，无需支付任何罚金。在此之后，我们不会退款，但您可以随时取消订阅。请阅读我们完整的退款政策。
有助学金吗？
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
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.
完成课程后，我会获得大学学分吗？
此课程不提供大学学分，但部分大学可能会选择接受课程证书作为学分。查看您的合作院校，了解详情。Coursera 上的在线学位和 Mastertrack™ 证书提供获得大学学分的机会。
还有其他问题吗？请访问 学生帮助中心。
