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.
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Университет ДьюкаОб этом курсе
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Прибл. 14 часов на выполнение
Английский
Субтитры: Арабский, Французский, Португальский (Европа), Итальянский, Вьетнамский, Корейский, Немецкий, Русский, Английский, Испанский
Приобретаемые навыки
- Statistics
- R Programming
- Rstudio
- Exploratory Data Analysis
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Начальный уровень
Прибл. 14 часов на выполнение
Английский
Субтитры: Арабский, Французский, Португальский (Европа), Итальянский, Вьетнамский, Корейский, Немецкий, Русский, Английский, Испанский
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Университет Дьюка
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.
Программа курса: что вы изучите
12 минут на завершение
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.
12 минут на завершение
1 видео ((всего 2 мин.)), 1 материал для самостоятельного изучения
2 ч. на завершение
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.
2 ч. на завершение
6 видео ((всего 28 мин.)), 2 материалов для самостоятельного изучения, 2 тестов
1 ч. на завершение
Introduction to Data Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
1 ч. на завершение
2 материалов для самостоятельного изучения
2 ч. на завершение
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.
2 ч. на завершение
7 видео ((всего 46 мин.)), 3 материалов для самостоятельного изучения, 2 тестов
Рецензии
- 5 stars78,29 %
- 4 stars17,35 %
- 3 stars2,44 %
- 2 stars0,64 %
- 1 star1,25 %
Лучшие отзывы о курсе INTRODUCTION TO PROBABILITY AND DATA WITH R
от партнера KN3 июня 2018 г.
The course is pretty nice, I learned some new statistics concepts although the knowledge is not so in-depth. The course also needs more tutorials on R. However, the assignments are quite good
от партнера BB3 сент. 2019 г.
Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.
от партнера SN11 мар. 2019 г.
This course was quite helpful for someone who like me who doesn't have a strong understanding of statistics. The highlight of the course was learning a new data analysis tool - R and RStudio.
от партнера AA24 февр. 2021 г.
I always wanted to learn statistics from scratch, but I never had a good university teacher. Here I found a good teacher and also the opportunity to learn whenever I want ( and skipping parts I knew!)
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Что я получу, оформив подписку на специализацию?
Можно ли получить финансовую помощь?
Will I receive a transcript from Duke University for completing this course?
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