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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/probability-intro
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课程名称：概率与数据导论（使用R） 课程概述：本课程将引导你学习抽样和数据探索的基本技巧，以及基本的概率理论和贝叶斯规则。你将探讨不同类型的抽样方法，并讨论这些方法如何影响推断的范围。课程涵盖多种探索性数据分析技术，包括数值汇总统计与基本数据可视化。你将学习安装并使用R与RStudio（免费的统计软件），并在实验练习和最终项目中应用这些软件。课程中所涉及的概念和技术将是后续推断与建模课程的基础。 课程大纲： - 介绍概率与数据：学习设计研究，使用数值汇总和可视化探索数据，学习概率规则及常用的概率分布。 - 数据项目介绍：使用R和RStudio完成作业。 - 探索性数据分析与推断入门：深入分析数值和分类数据，并介绍推断概念。 - 概率介绍：讨论概率、条件概率、贝叶斯定理，并轻微涉及贝叶斯推断。 - 概率分布：介绍正常分布与二项分布，完成初步数据分析项目。 参与方式：课程欢迎你灵活参与，鼓励积极参与论坛讨论，分享反馈与见解，增强学习体验。课程提供开放资源链接和补充阅读材料，帮助你深入理解课程内容，并通过每周的小测验与实验作业评估你对学习内容的掌握。
Name:About Introduction to Probability and Data
Description: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.
Name:Introduction to Data
Description: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.
Name:Introduction to Data Project
Description:To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
Name:Exploratory Data Analysis and Introduction to Inference
Description: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.
Name:Exploratory Data Analysis and Introduction to Inference Project
Description:To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
Name:Introduction to Probability
Description: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.
Name:Introduction to Probability Project
Description:To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
Name:Probability Distributions
Description: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). Also this week, you will be asked to complete an initial data analysis project with a real-world data set. The project is designed to help you discover and explore research questions of your own, using real data and statistical methods we learn in this class. Please read the project instructions to complete this self-assessment.
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.
