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4.7
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次における5の1コース

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初級レベル

約22時間で修了

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

英語

字幕:英語, 韓国語

習得するスキル

StatisticsR ProgrammingRstudioExploratory Data Analysis

次における5の1コース

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

初級レベル

約22時間で修了

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

英語

字幕:英語, 韓国語

シラバス - 本コースの学習内容

1
12分で修了

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>...
1件のビデオ (合計2分), 1 reading
1件のビデオ
1件の学習用教材
More about Introduction to Probability and Data10 分
1時間で修了

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>...
6件のビデオ (合計28分), 2 readings, 2 quizzes
6件のビデオ
Data Basics5 分
Observational Studies & Experiments4 分
Sampling and sources of bias8 分
Experimental Design2 分
(Spotlight) Random Sample Assignment3 分
2件の学習用教材
Lesson Learning Objectives10 分
Suggested Readings and Practice10 分
2の練習問題
Week 1 Practice Quiz10 分
Week 1 Quiz14 分
1時間で修了

Introduction to Data Project

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud....
2 readings, 1 quiz
2件の学習用教材
About Lab Choices (Read Before Selection)10 分
Week 1 Lab Instructions (RStudio)10 分
1の練習問題
Week 1 Lab: Introduction to R and RStudio16 分
2
2時間で修了

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>...
7件のビデオ (合計46分), 3 readings, 2 quizzes
7件のビデオ
Measures of Center4 分
Measures of Spread6 分
Robust Statistics1 分
Transforming Data3 分
Exploring Categorical Variables8 分
Introduction to Inference12 分
3件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Suggested Readings and Practice10 分
2の練習問題
Week 2 Practice Quiz10 分
Week 2 Quiz12 分
1時間で修了

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 readings, 1 quiz
2件の学習用教材
Week 2 Lab Instructions (RStudio)10 分
Week 2 Lab Instructions (RStudio Cloud)10 分
1の練習問題
Week 2 Lab: Introduction to Data20 分
3
2時間で修了

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>...
9件のビデオ (合計82分), 3 readings, 2 quizzes
9件のビデオ
Disjoint Events + General Addition Rule9 分
Independence9 分
Probability Examples9 分
(Spotlight) Disjoint vs. Independent2 分
Conditional Probability12 分
Probability Trees10 分
Bayesian Inference14 分
Examples of Bayesian Inference7 分
3件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Suggested Readings and Practice10 分
2の練習問題
Week 3 Practice Quiz6 分
Week 3 Quiz10 分
1時間で修了

Introduction to Probability Project

To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud....
2 readings, 1 quiz
2件の学習用教材
Week 3 Lab Instructions (RStudio)10 分
Week 3 Lab Instructions (RStudio Cloud)10 分
1の練習問題
Week 3 Lab: Probability10 分
4
2時間で修了

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>...
6件のビデオ (合計67分), 4 readings, 2 quizzes
6件のビデオ
Evaluating the Normal Distribution2 分
Working with the Normal Distribution5 分
Binomial Distribution17 分
Normal Approximation to Binomial14 分
Working with the Binomial Distribution9 分
4件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Suggested Readings and Practice10 分
Data Analysis Project Example10 分
2の練習問題
Week 4 Practice Quiz14 分
Week 4 Quiz14 分
4.7
651件のレビューChevron Right

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人気のレビュー

by 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.

by 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

デューク大学(Duke University)について

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....

Statistics with Rの専門講座について

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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