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.

提供方

## 课程信息

### 学生职业成果

## 33%

## 30%

## 11%

### 您将获得的技能

### 学生职业成果

## 33%

## 30%

## 11%

#### 可分享的证书

#### 100% 在线

#### 第 1 门课程（共 5 门）

#### 可灵活调整截止日期

#### 初级

#### 完成时间大约为22 小时

#### 英语（English）

### 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 个阅读材料**

**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**

**2 个阅读材料**

**2 个练习**

**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**

**1 个练习**

**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**

**3 个阅读材料**

**2 个练习**

**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**

**1 个练习**

**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**

**3 个阅读材料**

**2 个练习**

**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**

**1 个练习**

**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**

**4 个阅读材料**

**2 个练习**

### 审阅

#### 4.7

##### 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.

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.

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.

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

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.

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!

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.

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

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.

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.

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.

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

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.

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.

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!!!

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!

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.

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

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.

The videos of the course should show more R coding.\n\nThe assignments are too long, they take ages to review.\n\nThe explanation of the statistical concepts are excellent! Great job!

## 关于 Statistics with R 专项课程

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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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