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初級

完成時間大約為22 小時

建議:5 weeks of study, 5-7 hours/week...

英語(English)

字幕:英語(English), 韓語

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StatisticsR ProgrammingRstudioExploratory Data Analysis

第 1 門課程(共 1 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

初級

完成時間大約為22 小時

建議:5 weeks of study, 5-7 hours/week...

英語(English)

字幕:英語(English), 韓語

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 12 分鐘

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.

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1 個視頻 (總計 2 分鐘), 1 個閱讀材料
1 個視頻
1 個閱讀材料
More about Introduction to Probability and Data10分鐘
完成時間為 1 小時

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 (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.

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6 個視頻 (總計 28 分鐘), 2 個閱讀材料, 2 個測驗
6 個視頻
Data Basics5分鐘
Observational Studies & Experiments4分鐘
Sampling and sources of bias8分鐘
Experimental Design2分鐘
(Spotlight) Random Sample Assignment3分鐘
2 個閱讀材料
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 1 Practice Quiz10分鐘
Week 1 Quiz14分鐘
完成時間為 1 小時

Introduction to Data Project

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.

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2 個閱讀材料, 1 個測驗
2 個閱讀材料
About Lab Choices (Read Before Selection)10分鐘
Week 1 Lab Instructions (RStudio)10分鐘
1 個練習
Week 1 Lab: Introduction to R and RStudio16分鐘
2
完成時間為 2 小時

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.

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7 個視頻 (總計 46 分鐘), 3 個閱讀材料, 2 個測驗
7 個視頻
Measures of Center4分鐘
Measures of Spread6分鐘
Robust Statistics1分鐘
Transforming Data3分鐘
Exploring Categorical Variables8分鐘
Introduction to Inference12分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 2 Practice Quiz10分鐘
Week 2 Quiz12分鐘
完成時間為 1 小時

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.

...
2 個閱讀材料, 1 個測驗
2 個閱讀材料
Week 2 Lab Instructions (RStudio)10分鐘
Week 2 Lab Instructions (RStudio Cloud)10分鐘
1 個練習
Week 2 Lab: Introduction to Data20分鐘
3
完成時間為 2 小時

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.

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9 個視頻 (總計 82 分鐘), 3 個閱讀材料, 2 個測驗
9 個視頻
Disjoint Events + General Addition Rule9分鐘
Independence9分鐘
Probability Examples9分鐘
(Spotlight) Disjoint vs. Independent2分鐘
Conditional Probability12分鐘
Probability Trees10分鐘
Bayesian Inference14分鐘
Examples of Bayesian Inference7分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 3 Practice Quiz6分鐘
Week 3 Quiz10分鐘
完成時間為 1 小時

Introduction to Probability Project

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.

...
2 個閱讀材料, 1 個測驗
2 個閱讀材料
Week 3 Lab Instructions (RStudio)10分鐘
Week 3 Lab Instructions (RStudio Cloud)10分鐘
1 個練習
Week 3 Lab: Probability10分鐘
4
完成時間為 2 小時

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 (https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1).

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6 個視頻 (總計 67 分鐘), 4 個閱讀材料, 2 個測驗
6 個視頻
Evaluating the Normal Distribution2分鐘
Working with the Normal Distribution5分鐘
Binomial Distribution17分鐘
Normal Approximation to Binomial14分鐘
Working with the Binomial Distribution9分鐘
4 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
Data Analysis Project Example10分鐘
2 個練習
Week 4 Practice Quiz14分鐘
Week 4 Quiz14分鐘
4.7
685 個審閱Chevron Right

35%

完成這些課程後已開始新的職業生涯

31%

通過此課程獲得實實在在的工作福利

12%

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來自Introduction to Probability and Data的熱門評論

創建者 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.

創建者 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.

講師

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Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

關於 杜克大学

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....

關於 Statistics with R 專項課程

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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