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Kursteilnehmer-Bewertung und -Feedback für Inferential Statistics von Duke University

1,435 Bewertungen
263 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...



Mar 01, 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!


Aug 24, 2017

This course by Professor ?etinkaya-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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226 - 250 von 258 Bewertungen für Inferential Statistics

von Shahin A

Oct 01, 2016

Some parts are needed more clarification. In other words, as a student of the course you need to go beyond the materials, since the materials are not self-sufficient. Specially about simulation methods. However, this is not the reason that I give the course 4 out of 5. The absence of any help from TAs, based on my experience, is the reason. I expected some official replies to my question while there are only a few question for each week of the course.

von Richard N B A

Jun 19, 2016

Thorough treatment of the topics with great examples using real data. On the down side, the treatment of the mathematics behind the formulas is a little light. Great use of simulation to support the theory or to use when theoretical assumptions are not met. Strongly recommended!

von Farsan

Sep 29, 2016

Very good introductory course for inferential statistics. It is wise to complete the first course Introduction to Probability and Data of this specialization before enrolling into this one to grasp the concepts.

von Ananda R

Mar 13, 2017


von Yuzi H

Dec 28, 2017

It is very difficult...

von Abiodun B

Mar 28, 2017

This course gave me the toughest time of my life. I did the course for 3 months, i failed project once but i thank God, i proved toughest by passing with 100%.

von Markus K

Aug 18, 2017

Good videos, good book with exercises but many useful functions in R were not introduced (e.g. t.test()).

von José M C

Jan 04, 2017

Very useful tools for inference

von Nathan H

Dec 26, 2017

I wish there was more exposure to R.

von Mani G

Jun 09, 2017

some topics require more explanation!

von Robert F

Aug 08, 2016

Nice introduction to statistical inference concepts and techniques

von Paul N

Aug 17, 2016

The teaching is good, the course is a little heavy and a lot to take in in the later weeks. But, as a further grounding for statistics and R, I would very much recommend it.

von mnavidad

Jun 15, 2018

This course is great learn a lot well explained, the professor is great!!!

von Takahiro M

Mar 05, 2017

This is great course as Intro to Statistics

von joao b p d s

Mar 09, 2018


von Shalabh S

Jun 01, 2017

Very nice coarse for learning methods of inferential statistics.

von Dgo D

Feb 22, 2017

Its a very good way to introduce to R language

von Robert S

Dec 27, 2017

Very good material which gives practical knowledge supported by interesting examples. The only concern is that it is slightly shallow - lacking some mathematical justification for the given "rules of thumb" and theorems.


Mar 06, 2018

Need to revisit few classes as it was little aggressive.

von Natalie R

May 21, 2019

Well-taught, but they need to provide more resources to help people learn R. R is not a user-friendly app and I needed to google how to do a lot of the things they're asking us to do. Needless to say, I can google how to work in R on my own without paying Coursera a fee.

von dumessi

Aug 13, 2019

It is a great course, while some underlying logics are not clearly explained. And the quiz has some unexplained context, which is confused.

von Raffaele S

Nov 08, 2018

The fundamental concepts of statistics are well explained, however the exercises involvig R are kinda rushed up. Moreover, the R part is accomplished mainly by a library, dplyr, and the main concepts of R as a programming language are skipped. Finally, the peer grade review is a little more advanced than the course lessons and takes really a painful process - but this is a common problem in coursera.

von Mark N

Jul 18, 2018

great instruction on statistics, but no lectures on R. The R portion of the class is given as a lab at the end of each week.

von Luke F

May 18, 2017

The lady could have used a bit more rehearsing before recording.

von Dong J Y

Jul 29, 2017

I think this course needs more instruction with the R studio lab