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Bewertung und Feedback des Lernenden für Inferenzstatistik von Duke University

2,533 Bewertungen

Über den Kurs

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. 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 course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data...



23. Aug. 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!


28. Feb. 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

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351 - 375 von 445 Bewertungen für Inferenzstatistik

von EXAL G S

16. Feb. 2017


von Beatriz M A

22. Aug. 2022



23. Apr. 2021

So great

von Alfredo J N

10. Feb. 2019


von Raj K P

18. Sep. 2017

good one

von gerardo r g

22. Juli 2019


von guangyuan l

2. Aug. 2018


von Jeff G D

10. Aug. 2016


von Lerner Z

17. Sep. 2020


von Lucia F M D C

15. Juli 2021


von Praveen S

3. Juni 2020


von Charles G

20. Jan. 2018


von Jenard J P P

5. Feb. 2021


von Gonzalo C S

24. Juli 2016


von John C L R

19. Apr. 2021


von Sanan I

4. Juni 2020


von Saravanan V

31. Jan. 2019


von Radoslaw T

18. März 2018


von Emanuele M

18. Aug. 2020

Overall a great course. Very rich in material. I do not have a strong math or statistical background and i struggled a bit with the range and quantity of material presented. Hard work is surely involved, but it is ultimately rewarding. A word of caution : if you are taking this course standalone (or as part of Coursera's Data Science Learning Path like me) without taking the first introductory part, you will have to compensate a bit on the programming parts if you are new to R (luckily a lot of freely available instructional material is found on the web, and the professor herself offers a free statistics textbook with online R labs). Not a downside for me, as this course has made me discover this fantastic language which has taken a strong position besides my budding Python skills. Cheers!

von Wu X

7. Apr. 2020

I gave this course 4 stars. The missing 1 star is because this course has no content about R (but it is in a specialization called "statistics and R"). This course is only about statistics and the videos and instructor is good. The instructor explained the complex concepts well. At the end of the course, you need to do a project with Rstudio. I had no idea how to clean and manipulate the dataset and I had to drop out this course for sometime and register an account in another online education platform for programming for R specifically and learn how to handle those string, manipulate the datagrams and tables and extract the data I need from a dataset with thousands of variables. And then I got back to this project with more confidence and finally finished that.

von Gabriel V

1. Aug. 2022

It is a very interesting take on inferential statistics. The statistics is taugth at introductory level, using the book Open Statistics that has been introduced in the first course in the series. Regarding the software, the course continues on the use of R and the tidyverse. I understand pipes and are comfortable in R, but I think it may be a little bit confusing if it is your first rodeo with the software.

I'd recomend to include more resources about R in the course materials, or including those on the Open Statistics book. Also the book has many examples, but I would add at the end of the chapter a summary of the theory and formulas, since it is difficult to browse for refreshing the knowledge.

von Gayatri L

9. März 2022

I think overall this course was pretty good in explaining the concepts. Probably the best I've seen yet on this topic ans no other course I've even taken has helped me this much.

The only reason why I'm not giving it 5 stars is because I think they haven't taught much in terms of R. I think anyone who doesn't have any background on R at all might struggle with comlpeting the peer assignments and even the R sections in this course. I have a very basic idea so it helped a little but even I left it wsas an uphill battle there.

Still overall it's a course I would recommend to everyone just because of how well things are explained in this course. Everything is really very well sought out.

von Jason L

1. Jan. 2021

This is a great course and Professor Çetinkaya-Rundel is a fantastic teacher. I feel much more confident with statistical concepts and really feel confident with calculating statistical tests by hand.

However, I feel less confident with the R part of the course. I often found myself having to Google functions to figure out how they worked. I would have appreciated more focus on R within the lectures themselves and not just in the labs. Other than that, this was a wonderful course and I learned so much.

von Fernando M M E

3. Juli 2021

A very useful course to refresh inferential statistics. If you don't have a minimal knowledge or if you don't remember anything, you will need more time to complete it. The book is clear and there are a lot of exercises, but if you read it and you do the exercises you will need much more time. For those doing it for the data science learning path, R is not very well explained, because this is the second course in a specialization of five courses in Statistics with R. The teacher teaches well.

von Lucy M

22. Mai 2020

Well structured course to take at your own pace. I did a stats course about 5 years ago and this has been a good refresher - not sure how hard it would be for a total novice - i think it would take more time than suggested. Warning, if like me you have prior experience in R the assignments will take a little more figuring out too. The discussion forums have most the answers and help you need and actually the peer-review is really helpful to 'learn by teaching'.