课程信息

147,165 次近期查看

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

可灵活调整截止日期

根据您的日程表重置截止日期。

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。

初级

完成时间大约为16 小时

英语（English）

字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）

对员工进行热门技能培训能否为您的公司带来益处？

体验 Coursera 企业版

您将获得的技能

Statistical Inference
Statistical Hypothesis Testing
R Programming

可灵活调整截止日期

根据您的日程表重置截止日期。

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。

初级

完成时间大约为16 小时

英语（English）

字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）

对员工进行热门技能培训能否为您的公司带来益处？

体验 Coursera 企业版

授课教师

授课教师评分

4.77/5 （251 个评分）

Mine Çetinkaya-Rundel

Associate Professor of the Practice

Department of Statistical Science

345,555 个学生

7 门课程

授课大纲 - 您将从这门课程中学到什么

内容评分93%（8,294 个评分）

周

1

周 1

完成时间为 20 分钟

About the Specialization and the Course

This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Inferential Statistics. Please take several minutes to browse them through. Thanks for joining us in this course!

完成时间为 20 分钟

2 个阅读材料

周

2

周 2

完成时间为 4 小时

Central Limit Theorem and Confidence Interval

Welcome to Inferential Statistics! In this course we will discuss Foundations for Inference. Check out the learning objectives, start watching the videos, and finally work on the quiz and the labs of this week. In addition to videos that introduce new concepts, you will also see a few videos that walk you through application examples related to the week's topics. In the first week we will introduce Central Limit Theorem (CLT) and confidence interval.

完成时间为 4 小时

7 个视频（总计 65 分钟）, 6 个阅读材料, 3 个测验

7 个视频

Introduction4分钟

Sampling Variability and CLT20分钟

CLT (for the mean) examples10分钟

Confidence Interval (for a mean)11分钟

Accuracy vs. Precision7分钟

Required Sample Size for ME4分钟

CI (for the mean) examples5分钟

6 个阅读材料

Lesson Learning Objectives10分钟

Week 1 Suggested Readings and Practice Exercises10分钟

About Lab Choices10分钟

Week 1 Lab Instructions (RStudio)10分钟

Week 1 Lab Instructions (RStudio Cloud)10分钟

3 个练习

Week 1 Practice Quiz30分钟

Week 1 Quiz30分钟

Week 1 Lab30分钟

周

3

周 3

完成时间为 3 小时

Inference and Significance

Welcome to Week Two! This week we will discuss formal hypothesis testing and relate testing procedures back to estimation via confidence intervals. These topics will be introduced within the context of working with a population mean, however we will also give you a brief peek at what's to come in the next two weeks by discussing how the methods we're learning can be extended to other estimators. We will also discuss crucial considerations like decision errors and statistical vs. practical significance. The labs for this week will illustrate concepts of sampling distributions and confidence levels.

完成时间为 3 小时

7 个视频（总计 59 分钟）, 5 个阅读材料, 3 个测验

7 个视频

Another Introduction to Inference4分钟

Hypothesis Testing (for a mean)14分钟

HT (for the mean) examples9分钟

Inference for Other Estimators10分钟

Decision Errors8分钟

Significance vs. Confidence Level6分钟

Statistical vs. Practical Significance7分钟

5 个阅读材料

Lesson Learning Objectives10分钟

Week 2 Suggested Readings and Practice Exercises10分钟

Week 2 Lab Instructions (RStudio)10分钟

Week 2 Lab Instructions (RStudio Cloud)10分钟

3 个练习

Week 2 Practice Quiz30分钟

Week 2 Quiz16分钟

Week 2 Lab30分钟

周

4

周 4

完成时间为 4 小时

Inference for Comparing Means

Welcome to Week Three of the course! This week we will introduce the t-distribution and comparing means as well as a simulation based method for creating a confidence interval: bootstrapping. If you have questions or discussions, please use this week's forum to ask/discuss with peers.

完成时间为 4 小时

11 个视频（总计 84 分钟）, 5 个阅读材料, 3 个测验

11 个视频

Introduction4分钟

t-distribution7分钟

Inference for a mean9分钟

Inference for comparing two independent means8分钟

Inference for comparing two paired means9分钟

Power11分钟

Comparing more than two means6分钟

ANOVA9分钟

Conditions for ANOVA2分钟

Multiple comparisons6分钟

Bootstrapping8分钟

5 个阅读材料

Lesson Learning Objectives10分钟

Week 3 Suggested Readings and Practice Exercises10分钟

Week 3 Lab Instructions (RStudio)10分钟

Week 3 Lab Instructions (RStudio Cloud)10分钟

3 个练习

Week 3 Practice Quiz30分钟

Week 3 Quiz30分钟

Week 3 Lab30分钟

审阅

4.8

442 条评论

5 stars
83.30%
4 stars
13.17%
3 stars
1.98%
2 stars
0.60%
1 star
0.92%

来自推论统计的热门评论

由 PM 提供Dec 12, 2017

Very well taught. Student given an opportunity to explore and search for ways to solve problems by themselves. Professor (mentor) and other students always ready to help should you get stuck!

由 GP 提供Jan 7, 2021

The final project does not help, for example someone used discrete data 1,2,3,4,5 .... ,40 to compute a p.value as if it was normal. It is too general and does not fill the purpose of the course.

由 HS 提供Jul 5, 2020

Very nicely designed course and it also progresses very well. If higher mathematics would be involved in it, the course has the ability to replace many college's statistical inference's classes.

由 DS 提供Mar 7, 2017

This course is an excellent overview of inferential statistic tests / hypothesis tests and confidence intervals. The organization and material is quite good, with exercises and applications using R.

查看所有评论

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。
有助学金吗？
是的。如果您负担不起学习计划的注册费，则可以在选择学习计划时申请助学金或奖学金。如果您选择的学习计划提供助学金或奖学金，则您将在描述页面上看到一个申请链接。
Cost of the Course
If you want to complete the course and earn a Course Certificate by submitting assignments for a grade, you can upgrade your experience by subscribing to the course for $49/month. You can also apply for financial aid if you can't afford the course fee.
When you enroll in a course that is part of a Specialization (which this course is), you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses or cancel your subscription once you complete the single course.
Can I just enroll in a single course? I'm not interested in the entire Specialization.
To enroll in an individual course, search for the course title in the catalog.
To get full access to a course, including the option to earn grades and a Course Certificate, you'll need to subscribe. New subscribers will start with a full access subscription, which includes full access to every course in the Coursera catalog. Existing Specialization subscribers will be given the option to update to a full access subscription when enrolling in a new Specialization or course.
When you enroll in a course that is part of a Specialization, you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses.
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.

还有其他问题吗？请访问学生帮助中心。

推论统计

课程信息

您将获得的技能