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4.8

stars

1,563 Bewertungen

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281 Bewertungen

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...

Aug 24, 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!!!

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!

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von Shalabh S

•Jun 01, 2017

Very nice coarse for learning methods of inferential statistics.

von Aravindan

•Sep 03, 2018

Very well structured.Could focus on R programming a bit more!

von Jingyi Y

•Oct 30, 2019

No tutor answering questions in the discussion platform.

von VEERARAGHAVAN V

•Mar 06, 2018

Need to revisit few classes as it was little aggressive.

von Dgo D

•Feb 22, 2017

Its a very good way to introduce to R language

von SAURAV P

•Oct 29, 2016

good powerful insight into statistics. Thanks!

von Takahiro M

•Mar 05, 2017

This is great course as Intro to Statistics

von Mani G

•Jun 09, 2017

some topics require more explanation!

von Nathan H

•Dec 26, 2017

I wish there was more exposure to R.

von José M C

•Jan 04, 2017

Very useful tools for inference

von Yuzi H

•Dec 28, 2017

It is very difficult...

von Ananda R

•Mar 13, 2017

excellent

von joao b p d s

•Mar 09, 2018

excelent

von Shawn G

•Apr 20, 2017

I would give it a 3.5, with the extra 0.5 because of the great interaction, ease of use, and clarity of progress. It was pretty hard for me and I barely made it in under the deadline (jumping session to session to complete). You definitely need some R background by the end for the project. I expected to get more in information in using R for inferential statistics too... though there was a presentation and each lesson had followup for use in R. Great use of examples for each section. That helped me a lot.

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 Cezary K

•Jun 30, 2017

For me there is not much more than u could learn in comparison to previous course. Would expect some more knowledge from this course

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 Dong J Y

•Jul 29, 2017

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

von Luke F

•May 18, 2017

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

von Willian W

•Apr 01, 2018

Too much basic

von Evren O

•Jun 02, 2019

At times it feels lazy how it is put together. The examples are confusing (rather than clarifying) and there is close to no teaching of R, but the assignments are meant to be done on it. In fact in the forums it is endorsed by mentors to learn R somewhere else. Likewise, I saw one comment where the student mentioned how they got confused by a core concept (p-value) and could finally wrap their head around it by watching a Khan Academy video. And sadly, this was also endorsed by a mentor. Overall, I found the effort put into this course insufficient for people who are new to Statistics or R. Therefore, the name of the entire specialization becomes misleading as it suggests that we were going to be taught how to use R in statistics. I had high hopes for this course but sadly I will abandon it and spend my money on an alternative course/specialization.

von Desmond H

•Sep 11, 2016

So much disjointed information.... I felt absolutely crushed trying to learn and understand all this. Am waiting for another 8 hours before I can reattempt the quiz.

Personally, I feel that this course assumes the student is automatically an expert in statistics (simply due to completing the first intro to statistics course). The logical progression of how to approach different problems - and the terminology of the statements involved has been thrown out the window...

If you're new to statistics, I suggest you should at least double the time allocation they provided...

von Yan Z

•Jan 22, 2017

The teacher lacks the ability of mathematical description, including clearing defining concepts, describing everything in mathematical languages, and showing math formulas of t-tests. She hopes to hide everything behind the canvas and just show how statistics are applied. But without enough mathematics nothing she said makes sense. I have to search on the internet to get to know what she didn't teach.

------from a math phd.

von Syed S R

•Sep 13, 2018

Not suitable for beginners

von farzad s

•Jul 25, 2019

awful!!