课程信息
4.7
2,593 个评分
584 个审阅
专项课程

第 1 门课程(共 5 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
初级

初级

完成时间(小时)

完成时间大约为21 小时

建议:5 weeks of study, 5-7 hours/week...
可选语言

英语(English)

字幕:英语(English), 韩语

您将获得的技能

StatisticsR ProgrammingRstudioExploratory Data Analysis
专项课程

第 1 门课程(共 5 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
初级

初级

完成时间(小时)

完成时间大约为21 小时

建议:5 weeks of study, 5-7 hours/week...
可选语言

英语(English)

字幕:英语(English), 韩语

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 12 分钟

About Introduction to Probability and Data

<p>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.<p>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 <a href="https://leanpub.com/openintro-statistics/" target="_blank">OpenIntro Statistics, 3rd Edition</a> (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.<p>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 <a href="https://www.coursera.org/learn/probability-intro/resources/crMc4" target="_blank">resource page</a> listing useful resources for this course. <p>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.</p>...
Reading
1 个视频 (总计 2 分钟), 1 个阅读材料
Video1 个视频
Reading1 个阅读材料
More about Introduction to Probability and Data10分钟
完成时间(小时)
完成时间为 2 小时

Introduction to Data

<p>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 <a href="https://www.coursera.org/learn/probability-intro/module/rQ9Al/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this module's forum</b></a> and discuss with your peers! To get started, view the <a href="https://www.coursera.org/learn/probability-intro/supplement/rooeY/lesson-learning-objectives" target="_blank"><b>learning objectives</b></a> of Lesson 1 in this module.</p>...
Reading
7 个视频 (总计 30 分钟), 5 个阅读材料, 3 个测验
Video7 个视频
Data Basics5分钟
Observational Studies & Experiments4分钟
Sampling and sources of bias8分钟
Experimental Design2分钟
(Spotlight) Random Sample Assignment3分钟
DataCamp Instructions2分钟
Reading5 个阅读材料
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
About Lesson Choices (Read Before Selection)10分钟
Week 1 Lab Instructions (RStudio)10分钟
Week 1 Lab Instructions (DataCamp)10分钟
Quiz3 个练习
Week 1 Practice Quiz10分钟
Week 1 Quiz14分钟
Week 1 Lab: Introduction to R and RStudio16分钟
2
完成时间(小时)
完成时间为 3 小时

Exploratory Data Analysis and Introduction to Inference

<p>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. </p>...
Reading
7 个视频 (总计 46 分钟), 5 个阅读材料, 3 个测验
Video7 个视频
Measures of Center4分钟
Measures of Spread6分钟
Robust Statistics1分钟
Transforming Data3分钟
Exploring Categorical Variables8分钟
Introduction to Inference12分钟
Reading5 个阅读材料
Lesson Learning Objectives10分钟
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
Week 2 Lab Instructions (RStudio)10分钟
Week 2 Lab Instructions (DataCamp)10分钟
Quiz3 个练习
Week 2 Practice Quiz10分钟
Week 2 Quiz12分钟
Week 2 Lab: Introduction to Data20分钟
3
完成时间(小时)
完成时间为 3 小时

Introduction to Probability

<p>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. </p><p>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. </p>...
Reading
9 个视频 (总计 82 分钟), 5 个阅读材料, 3 个测验
Video9 个视频
Disjoint Events + General Addition Rule9分钟
Independence9分钟
Probability Examples9分钟
(Spotlight) Disjoint vs. Independent2分钟
Conditional Probability12分钟
Probability Trees10分钟
Bayesian Inference14分钟
Examples of Bayesian Inference7分钟
Reading5 个阅读材料
Lesson Learning Objectives10分钟
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
Week 3 Lab Instructions (RStudio)10分钟
Week 3 Lab Instructions (DataCamp)10分钟
Quiz3 个练习
Week 3 Practice Quiz6分钟
Week 3 Quiz10分钟
Week 3 Lab: Probability10分钟
4
完成时间(小时)
完成时间为 2 小时

Probability Distributions

<p>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 <b>no labs</b> for this week. Please don't hesitate to post any questions, discussions and related topics on <a href="https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this week's forum</b></a>.</p>...
Reading
6 个视频 (总计 67 分钟), 4 个阅读材料, 2 个测验
Video6 个视频
Evaluating the Normal Distribution2分钟
Working with the Normal Distribution5分钟
Binomial Distribution17分钟
Normal Approximation to Binomial14分钟
Working with the Binomial Distribution9分钟
Reading4 个阅读材料
Lesson Learning Objectives10分钟
Lesson Learning Objectives10分钟
Suggested Readings and Practice10分钟
Data Analysis Project Example10分钟
Quiz2 个练习
Week 4 Practice Quiz14分钟
Week 4 Quiz14分钟
4.7
584 个审阅Chevron Right
职业方向

29%

完成这些课程后已开始新的职业生涯
工作福利

26%

通过此课程获得实实在在的工作福利
职业晋升

14%

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热门审阅

创建者 AAJan 24th 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.

创建者 HDMar 31st 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.

讲师

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Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

关于 Duke University

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....

关于 Statistics with R 专项课程

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....
Statistics with R

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