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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課程信息
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學生職業成果
33%
完成這些課程後已開始新的職業生涯
30%
通過此課程獲得實實在在的工作福利
11%
加薪或升職
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 1 門課程（共 5 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為14 小時
英語（English）
字幕：英語（English）, 韓語
您將獲得的技能
StatisticsR ProgrammingRstudioExploratory Data Analysis
學生職業成果
33%
完成這些課程後已開始新的職業生涯
30%
通過此課程獲得實實在在的工作福利
11%
加薪或升職
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 1 門課程（共 5 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為14 小時
英語（English）
字幕：英語（English）, 韓語
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.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 12 分鐘
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.
完成時間為 12 分鐘
1 個視頻 （總計 2 分鐘）, 1 個閱讀材料
1 個閱讀材料
More about Introduction to Probability and Data10分鐘
完成時間為 2 小時
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.
完成時間為 2 小時
6 個視頻 （總計 28 分鐘）, 2 個閱讀材料, 2 個測驗
6 個視頻
Introduction3分鐘
Data Basics5分鐘
Observational Studies & Experiments4分鐘
Sampling and sources of bias8分鐘
Experimental Design2分鐘
(Spotlight) Random Sample Assignment3分鐘
2 個閱讀材料
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 1 Practice Quiz30分鐘
Week 1 Quiz30分鐘
完成時間為 1 小時
Introduction to Data Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
完成時間為 1 小時
2 個閱讀材料
2 個閱讀材料
About Lab Choices (Read Before Selection)10分鐘
Week 1 Lab Instructions (RStudio)10分鐘
1 個練習
Week 1 Lab: Introduction to R and RStudio30分鐘
完成時間為 2 小時
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.
完成時間為 2 小時
7 個視頻 （總計 46 分鐘）, 3 個閱讀材料, 2 個測驗
7 個視頻
Measures of Center4分鐘
Measures of Spread6分鐘
Robust Statistics1分鐘
Transforming Data3分鐘
Exploring Categorical Variables8分鐘
Introduction to Inference12分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 2 Practice Quiz30分鐘
Week 2 Quiz30分鐘
完成時間為 1 小時
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.
完成時間為 1 小時
2 個閱讀材料
2 個閱讀材料
Week 2 Lab Instructions (RStudio)10分鐘
Week 2 Lab Instructions (RStudio Cloud)10分鐘
1 個練習
Week 2 Lab: Introduction to Data30分鐘
完成時間為 3 小時
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.
完成時間為 3 小時
9 個視頻 （總計 82 分鐘）, 3 個閱讀材料, 2 個測驗
9 個視頻
Introduction5分鐘
Disjoint Events + General Addition Rule9分鐘
Independence9分鐘
Probability Examples9分鐘
(Spotlight) Disjoint vs. Independent2分鐘
Conditional Probability12分鐘
Probability Trees10分鐘
Bayesian Inference14分鐘
Examples of Bayesian Inference7分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 3 Practice Quiz30分鐘
Week 3 Quiz30分鐘
完成時間為 1 小時
Introduction to Probability Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
完成時間為 1 小時
2 個閱讀材料
2 個閱讀材料
Week 3 Lab Instructions (RStudio)10分鐘
Week 3 Lab Instructions (RStudio Cloud)10分鐘
1 個練習
Week 3 Lab: Probability30分鐘
完成時間為 3 小時
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).
完成時間為 3 小時
6 個視頻 （總計 67 分鐘）, 4 個閱讀材料, 2 個測驗
6 個視頻
Evaluating the Normal Distribution2分鐘
Working with the Normal Distribution5分鐘
Binomial Distribution17分鐘
Normal Approximation to Binomial14分鐘
Working with the Binomial Distribution9分鐘
4 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
Data Analysis Project Example10分鐘
2 個練習
Week 4 Practice Quiz30分鐘
Week 4 Quiz30分鐘
審閱
來自INTRODUCTION TO PROBABILITY AND DATA WITH R的熱門評論
由 AA 提供2018年1月23日
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 BB 提供2019年9月3日
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.
由 HD 提供2018年3月30日
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2017年6月9日
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.
關於 Statistics with R 專項課程
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.
常見問題
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。
Is financial aid available?
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.
還有其他問題嗎？請訪問 學生幫助中心。
