PP
5.0Reviewed Jan 21, 2019
The concepts are explained in a very simple and effective manner with the help of a case study. Background knowledge of R will be very handy if one wants to cover the topics at a faster rate.
Inferential Statistics
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
Status: Sampling (Statistics)
Status: Probability Distribution
BeginnerCourse16 hours
Featured reviews
GP
4.0Reviewed Jan 7, 2021
The final project does not help, for example someone used discrete data 1,2,3,4,5 .... ,40 to compute a p.value as if it was normal. It is too general and does not fill the purpose of the course.
ZQ
4.0Reviewed Nov 22, 2018
Very useful course about statistics. May need some fundamental understanding of statistics before, but through the clear explanation and examples, I've learnt a lot from this course
LD
5.0Reviewed Apr 28, 2020
This has been the second course in this specialization and things are going smoothly.The greatest thing is the final projects which give us freedom on what we want to figure out with given data set.
AW
5.0Reviewed Nov 1, 2017
I really enjoyed this course and found the professors lectures better structured and clearer. I also like (and needed) the variety of datasets she used for instruction. Thank you!!
DS
5.0Reviewed Mar 7, 2017
This course is an excellent overview of inferential statistic tests / hypothesis tests and confidence intervals. The organization and material is quite good, with exercises and applications using R.
HS
5.0Reviewed Jul 5, 2020
Very nicely designed course and it also progresses very well. If higher mathematics would be involved in it, the course has the ability to replace many college's statistical inference's classes.
MN
5.0Reviewed Feb 28, 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
5.0Reviewed Aug 23, 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!!!
SK
5.0Reviewed Jun 22, 2022
Excellent course and specialization. I have learnt a lot. Could you also add generalize linear regressoin including logistic, poisson, negative bionomial and survival analysis. Thanks,
AP
5.0Reviewed Apr 13, 2021
Professor has her unique way to explain the concept through various real life examples. I really enjoy the course the whole time. Can't wait to move on to the next course asap. Thanks!
PM
5.0Reviewed Dec 12, 2017
Very well taught. Student given an opportunity to explore and search for ways to solve problems by themselves. Professor (mentor) and other students always ready to help should you get stuck!