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.
Об этом курсе
Карьерные результаты учащихся
Прибл. 22 часа на выполнение
Карьерные результаты учащихся
Прибл. 22 часа на выполнение
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.
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Лучшие отзывы о курсе INTRODUCTION TO PROBABILITY AND DATA
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.
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.
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.
Good but questions lacked clarity in what is expected. i.e. "Work out the Boy to Girl ratio" - in what fashion do we do this, as it appeared to be the same as simply working out the "proportion of b
A good introductory course to data analysis, statistics and the R programming language. Recommended to people who are new to data analysis and also those who are experienced and could use a refresh.
The instructions for the final project need to be much clearer. I had a hard time figuring it out, and all of the projects I peer-edited were done poorly. Otherwise, I enjoyed the course very much!
The lectures were very clear and concise and the examples were very relevant. Some of the R instructions left a little something to be desired, but nothing a little time and google couldn't solve.
Really good content and the teacher is one of the best in Coursera. This is for many people a difficult subject that is made easy to digest. Looking forward to more courses from the same Teacher
The contents of the course about statistics are friendly to the beginners and easy to understand, however, the R learning is a little bit hard to those who have no computer or coding background.
Great course! Explained the concepts so clear and crisp and the exercises with R are great. The project reinforces all the concepts. All in all, a great course for beginners in statistics and R.
Great course - great guidance through RStudio coding. Would be great if the instructor could slow down a bit during lectures to make taking notes easier. Otherwise very happy with the course.
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
excellent course. lots of material to work off of. I wish there were more tutorials for the R language! I would love to learn more of the capabilities of the program through this online tool.
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.
The final project is quite challenging but I have learned so much from this course. The lecture is great and the professor explains each concept well with examples. Really worthy of taking!!!
Best statistical course ever taken!\n\nClear explanation with practical examples and background on the basis of the statistics applied. Highly recommend to anyone interested in statistics!
This is a very accessible intro to statistical analysis, light on math but heavy on intuition, and the R programming labs are a superb way to practice and really learn to apply the tools.
This was an excellent course, I found it easy to follow and I learned a lot that pertains directly to my career. I look forward to the other courses in the Statistics with R certificate
It was a great course. The videos were clear in the content and ideas. I personally struggled coming up with research questions for the project. But it was a great learning experience.
The videos of the course should show more R coding.\n\nThe assignments are too long, they take ages to review.\n\nThe explanation of the statistical concepts are excellent! Great job!
Специализация Statistics with R: общие сведения
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на специализацию?
Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Можно ли получить финансовую помощь?
Will I receive a transcript from Duke University for completing this course?
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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