Back to Inferential Statistics

4.8

stars

1,887 ratings

•

358 reviews

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...

MN

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!

ZC

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!!!

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By Amy W

•Dec 12, 2019

The course is well designed, and the examples given in each lesson are informative and interesting.

For the final project, I wanted to group some categories from one variable together in a new variable, but I did not have the code I needed to do it. It would have been very helpful to have that information in one of the labs prior to doing the final project.

By 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!

By Anna D

•May 22, 2017

I loved this course. As with the previous course a lot of things that weren't clear to me before are now. I totally recommend it to anybody new to statistics or anybody who is struggling with statistics (like I have for a very long time).

By 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.

By Farsan R

•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.

By robert p

•Aug 28, 2018

This course seemed unbalanced compared to some of the other courses and was very work-heavy. I felt it could have, or maybe should have been broken up into two courses, or that other courses should be longer.

By Amit C

•Feb 18, 2019

The course is very well explained I had to refer other materials for ANOVA technique to understand it better hence that part can be either improved OR more reference material be provided

By Zhang Q

•Nov 23, 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

By greena m s

•Jul 30, 2020

This is a wonderfully curated course if u follow the readings and practise suggestions. But the main issue is the R programming. It needs better practise than suggested readings.

By MEKALA S N

•Jun 10, 2020

Very good course on basic understanding of inferential statistics. Instructor was very clear in delivering the content. The lab work is very helpful in developing R knowledge.

By 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.

By Adara

•Oct 17, 2017

It is a very nice course, I have learned a lot. However, it is convenient to take the previous one of the specialization, as they base some examples or R knowledge on it.

By Stefano D V

•Jun 17, 2020

Without a background in confidence intervals and hypothesis testing, I think that it would be very difficoult to understand these concepts in those few videos.

By 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%.

By Sergio E T

•Jan 04, 2019

The inference function and hypotheses tests are really useful. Permutation tests need more explaining and examples; otherwise they should not be included.

By Aaron M

•Nov 28, 2019

A good course for learning statistical inference, though I found that more than a week per module was required to really absorb the content.

By 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.

By Lucía M F

•Apr 23, 2020

It was a very interesting and useful course. To improve it a little bit, I would focus more on the use of R to do different analysis.

By Janusz P

•Apr 29, 2018

I liked this course because it gives basic ideas how inferential statistics works, without going into mathematical details.

By Peter C

•Nov 19, 2018

I thought this course did a great job of incorporating R code into the lecture and hope that continues in future courses.

By Rohit D W

•Aug 14, 2020

An Introductory course with a lot of examples and a project at the end to furnish your concepts and knowledge.

By Richard M

•Mar 08, 2019

Generally a great course, but would benefit from a better explanation at times of how to use R effectively.

By Markus K

•Aug 18, 2017

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

By kirran

•Sep 06, 2018

More detailed answers on Quiz questions and some more explanation on R codes will help a lot

By Mikhail I

•Jul 16, 2020

good course overall. Would love to see more math exercises rather than wording of problems.

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