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Introduction to Probability and Data, Duke University

Оценки: 2,589
Рецензии: 583

Об этом курсе

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....

Лучшие рецензии

автор: AA

Jan 24, 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.

автор: HD

Mar 31, 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.

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Рецензии: 563

автор: Lindsay Carlson

Dec 13, 2018

This course was a good introduction to basic probability, experimental design, and data structure. The labs and final assignments made great use of R Studio and markdown. This course is best suited for someone who is proficient in R already.


Dec 11, 2018

One of the best course in Statistics.

автор: Samuel Omar Tovias Alanis

Dec 10, 2018

It's a great course, I had acquired new abilities like using R language programming for applied statistics, as well as knowledge about probability and statistics in topics like: sampling, measures of center and spread, data visualization, inference, probability distribution and much more.

автор: EthanKwon

Dec 04, 2018

Thanks to this course, I was able to develop my knowledge of statistics and get basic skills in R programming.


Dec 01, 2018

The final project should have an instructional video.

автор: Gunjari Bhattacharya

Nov 29, 2018

The course was taught in a very illustrative manner with enough repititions over the concepts! A very deep dive from absolute basics to how's and why's. The assignments related to coding can come with some clearer explanations and the project is a little beyond the scope of the coding taught, however it will be an intensive and incredibly helpful venture if completed.

автор: 舒穎 鄭

Nov 26, 2018

The lecturer is very nice and teaching well, the basic knowledge is easy to learn. Examples are vivid and easy to understand as well. The biggest problem is the final project. The things we learn can not support the ability to finish the project. One way to improve it is to give more tips or teach more usage of R. Overall I learnt many useful stuffs and I recommend it!

автор: Toan Thien Le

Nov 25, 2018

Great introduction course on Probability.

The final report is unexpectedly challenging when one has to come up with 3 analysis from a dataset with more than 100 variables.

So if you choose to finish this course, be prepare to spend a lot more time than other normal ones on Coursera.


Nov 23, 2018

The course is VERY helpful, I used all the things I learned from the course in my daily study, I feel more confident and committed to finish the specialization!

автор: Sergio Escalante Trejos

Nov 22, 2018

Good for fundamentals.