概率论与数据导论培训
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.
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 /learn/probability-intro/and discuss with your peers!
To get started, view the learning objectives
of Lesson 1 in this module.
Introduction to Data Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
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.
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.
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.
Introduction to Probability Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
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