# Statistics with R 专项课程

Master Statistics with R. Statistical mastery of data analysis including inference, modeling, and Bayesian approaches.

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### 您将获得的技能

## 关于此 专项课程

#### 可分享的证书

#### 100% 在线课程

#### 灵活的计划

#### 初级

无需相关领域的预备知识无需相关经验。

#### 完成时间大约为7 个月

#### 英语（English）

### 专项课程的运作方式

### 加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习，请直接注册专项课程，或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时，您将自动订阅整个专项课程。您可以只完成一门课程，您可以随时暂停学习或结束订阅。访问您的学生面板，跟踪您的课程注册情况和进度。

### 实践项目

每个专项课程都包括实践项目。您需要成功完成这个（些）项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程，则需要在开始之前完成其他所有课程。

### 获得证书

在结束每门课程并完成实践项目之后，您会获得一个证书，您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

### 此专项课程包含 5 门课程

### Introduction to Probability and Data

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.

### 推论统计

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. 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 course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data

### Linear Regression and Modeling

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

### 贝叶斯统计

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction.

### 关于 杜克大学

### 审阅

#### 4.6

##### 来自STATISTICS WITH R的热门评论

It is a very nice course, I have learned a lot. However, it is convenient to take the previous one of the specialization, as they base some examples or R knowledge on it.

The course is VERY helpful, I used all the things I learned from the course in my daily study, I feel more confident and committed to finish the specialization!

Great course. Quite difficult though. I wished it was split to two course or maybe an entire specialization dedicated for this.

Nice course. Comparing this course with the second and fourth ones in the specialization, this is a rather light-weighted one.

Thanks for the excellent course. The whole "Statistics with R" specialization is a perfect introduction in statistics.

Yet another superb course in this specialization.\n\nBe ready to spend lots of time and learn lots of things.

Great, comprehensive way to utilise all of skills obtained during this specialization!

This is a great course for this specialization but don't expect much depth.

## 常见问题

退款政策是如何规定的？

我可以只注册一门课程吗？

可以！点击您感兴趣的课程卡开始注册即可。注册并完成课程后，您可以获得可共享的证书，或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分，系统会自动为您订阅完整的专项课程。访问您的学生面板，跟踪您的进度。

有助学金吗？

我可以免费学习课程吗？

此课程是 100% 在线学习吗？是否需要现场参加课程？

此课程完全在线学习，无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

What background knowledge is necessary?

Basic math, no programming experience required. A genuine interest in data analysis is a plus!

In the later courses in the Specialization, we assume knowledge and skills equivalent to those which would have been gained in the prior courses (for example: if you decide to take course four, Bayesian Statistics, without taking the prior three courses we assume you have knowledge of frequentist statistics and R equivalent to what is taught in the first three courses).

Do I need to take the courses in a specific order?

Yes.

完成专项课程后我会获得大学学分吗？

Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

What if I already have a certificate from Data Analysis and Statistical Inference?

In this specialization, R is a requirement, and the labs have been enhanced and revised from the previous course. Success in the fourth course and the capstone project will depend heavily on successfully completing the first three courses in this specialization. Therefore, we require all students complete all courses to obtain the certificate.

Do I need specific software?

Yes. You will need R and RStudio. Both are free and publicly available. You will need administrator access to your computer to install this software.

还有其他问题吗？请访问 学生帮助中心。