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
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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11 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11 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 1 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 1 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 Quiz10分鐘
Week 1 Quiz14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 RStudio16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 Quiz10分鐘
Week 2 Quiz12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 Data20分鐘
完成時間為 2 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 2 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 Quiz6分鐘
Week 3 Quiz10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: Probability10分鐘
完成時間為 2 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 2 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 Quiz14分鐘
Week 4 Quiz14分鐘
審閱
4.7
來自INTRODUCTION TO PROBABILITY AND DATA的熱門評論
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 MM 提供Jul 5, 2019
Good but questions lacked clarity in what is expected. i.e. "Work out the Boy to Girl ratio" - in what fashion do we do this, as it appeared to be the same as simply working out the "proportion of b
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.
由 JH 提供Mar 26, 2020
The instructions for the final project need to be much clearer. I had a hard time figuring it out, and all of the projects I peer-edited were done poorly. Otherwise, I enjoyed the course very much!
由 HW 提供Dec 13, 2017
The lectures were very clear and concise and the examples were very relevant. Some of the R instructions left a little something to be desired, but nothing a little time and google couldn't solve.
由 SS 提供Jul 26, 2017
Great course! Explained the concepts so clear and crisp and the exercises with R are great. The project reinforces all the concepts. All in all, a great course for beginners in statistics and R.
由 SG 提供Jun 18, 2019
The contents of the course about statistics are friendly to the beginners and easy to understand, however, the R learning is a little bit hard to those who have no computer or coding background.
由 RR 提供Sep 17, 2016
Really good content and the teacher is one of the best in Coursera. This is for many people a difficult subject that is made easy to digest. Looking forward to more courses from the same Teacher
由 GL 提供Jun 16, 2019
The final project is quite challenging but I have learned so much from this course. The lecture is great and the professor explains each concept well with examples. Really worthy of taking!!!
由 SN 提供Mar 11, 2019
This course was quite helpful for someone who like me who doesn't have a strong understanding of statistics. The highlight of the course was learning a new data analysis tool - R and RStudio.
由 CD 提供Oct 10, 2016
excellent course. lots of material to work off of. I wish there were more tutorials for the R language! I would love to learn more of the capabilities of the program through this online tool.
由 HB 提供Oct 7, 2018
Great course - great guidance through RStudio coding. Would be great if the instructor could slow down a bit during lectures to make taking notes easier. Otherwise very happy with the course.
由 KN 提供Jun 3, 2018
The course is pretty nice, I learned some new statistics concepts although the knowledge is not so in-depth. The course also needs more tutorials on R. However, the assignments are quite good
由 TC 提供Apr 29, 2017
Best statistical course ever taken!\n\nClear explanation with practical examples and background on the basis of the statistics applied. Highly recommend to anyone interested in statistics!
由 BR 提供May 11, 2016
This is a very accessible intro to statistical analysis, light on math but heavy on intuition, and the R programming labs are a superb way to practice and really learn to apply the tools.
由 AS 提供Apr 5, 2020
It was very simple to understand, excellent teachers. I really enjoyed it! I use statistics on a daily basis and this consolidates my knowledge. Plus, it helps me enhance my skills at R.
由 RM 提供Jan 15, 2019
This was an excellent course, I found it easy to follow and I learned a lot that pertains directly to my career. I look forward to the other courses in the Statistics with R certificate
由 BB 提供Aug 20, 2017
It was a great course. The videos were clear in the content and ideas. I personally struggled coming up with research questions for the project. But it was a great learning experience.
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.
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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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