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Learner Reviews & Feedback for Inferential Statistics by Duke University

4.8
stars
2,650 ratings

About the Course

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 reviews

MN

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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!

GH

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This was hard; The Statistics part became harder and harder and the R part seemed to not keep up with it. You need to learn more R on your own, which is a challenge - there are man

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451 - 468 of 468 Reviews for Inferential Statistics

By Hans H

Aug 18, 2022

I had hope hoped to learn how to conduct inferential statistic in R, but the course focuses a lot on concepts and calculating everything by hand. I think that is good, but not enough. So even after completing the course I'm not able to conduct a ANOVA or calculate chi-statistics in. The quizzes are also very focused on definitions and conditions, containing very tricky wordings at times. So even though you can do all the calculations and you know the right answer, the right answer can be very difficult to identify.

By 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.

By Raffaele S

Nov 8, 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.

By Артур Л

May 1, 2024

Some examples were too complicated and only added complexity to understanding the material by delving into the context of the example.

By 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

By 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.

By Luke F

May 18, 2017

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

By Willian A

Mar 31, 2018

Too much basic

By Keith B L S

Apr 4, 2022

Good job!

By Pua, A C R

May 2, 2024

neat

By JERALD P N

Apr 22, 2021

Tutorial to use the program or software is fundamental in this course

By Alberto M

Jul 19, 2021

Nothing really works well and instructions are not clear.

By vivek d

Apr 29, 2021

will do it later , right too complicated

By Muneera M

Nov 6, 2021

please tel me how to enroll for free

By SachinVargheseBiju

Jul 18, 2020

very irritating

By Deleted A

Apr 21, 2021

putang ina

By farzad s

Jul 25, 2019

awful!!

By Raul R

Dec 9, 2019

pesimo