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Bewertung und Feedback des Lernenden für Inferenzstatistik von Duke University

4.8
Sterne
2,311 Bewertungen
424 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...

Top-Bewertungen

MN
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!

ZC
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!!!

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326 - 350 von 418 Bewertungen für Inferenzstatistik

von Prasenjit P

14. Sep. 2018

Superb !!!

von Gustavo G

22. Apr. 2017

I love it!

von Donal G

7. Jan. 2017

Very good.

von chenhyde628

20. Nov. 2016

very good.

von Sumedha S

1. Juli 2020

Thank you

von manuel e c e

27. Okt. 2017

Thank you

von EXAL G S

16. Feb. 2017

Excelente

von CABANGUNAY , M J (

23. Apr. 2021

So great

von Alfredo N

10. Feb. 2019

Amazing!

von Raj K P

18. Sep. 2017

good one

von gerardo r g

22. Juli 2019

awesome

von guangyuan l

2. Aug. 2018

amazing

von Jeff G D

10. Aug. 2016

5-star!

von Lerner Z

17. Sep. 2020

Great.

von Lucia F M D C

15. Juli 2021

great

von Praveen S

3. Juni 2020

Super

von Charles G

20. Jan. 2018

Great

von Jenard J P P

5. Feb. 2021

yeah

von Gonzalo C S

24. Juli 2016

Cool

von John C L R

19. Apr. 2021

g

von Sanan I

4. Juni 2020

.

von Saravanan

31. Jan. 2019

-

von Radoslaw T

18. März 2018

O

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.