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Learner Reviews & Feedback for Statistical Inference by Johns Hopkins University

4.2
3,473 ratings
672 reviews

About the Course

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data....

Top reviews

JA

Oct 26, 2018

Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .

AP

Mar 22, 2017

The strategy for model selection in multivariate environment should have been explained with an example. This will make the model selection process, interaction and its interpretation more clear.

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126 - 150 of 641 Reviews for Statistical Inference

By Offiong E

Jun 28, 2017

very fast paced course. i totally enjoyed digging deep into my inner reserve.

By danxu

May 22, 2016

Very useful !

Teacher is awesome, statement is clear and simple.

love this course!

By Maxim K

Feb 02, 2016

I like lesson, teacher on video don't quickly and easily explained.

By Alessandro S

Apr 03, 2018

This is a great course.

By Paul C

Feb 11, 2017

Kudos to Caffo for using charts and examples to provide a lot of insight without using a lot of math. However, I would personally like the math to be presented, too (e.g., the 'off-center' T-distribution, etc.). This could be done is special sections of the book and lectures, as is done in the Regression Models class.

By Pavel T

Jan 23, 2017

This course is exciting opportunity to "connect the dots" in introductory statistics. It is challenging, but very informative and engaging.

By Do H L

Jun 17, 2016

This course is tough, informative. Good for people who want a summary of all the statistical concepts you can use for data science. You'll get the most out of this course not by expecting it to be beginner, because it is not. This course is best supplemented by having background knowledge in statistics. Meaning, learners would be much better off if he/she did some statistical course before. This course will provide the practical experience of implementing statistical concepts in R.

By Harish V

Feb 01, 2017

Very helpful course

By Regis O

Aug 29, 2016

This course covers a wide range of powerful statistical concepts. The best way to work through this is to run R code as you go through the examples. If you are not comfortable with R, make sure to take the intro to R course first.

By Mohankumar S

May 24, 2017

Great explanation to work out.

By Divvya.T

Oct 30, 2017

Excellent course to take !!

By Long T

Sep 10, 2017

Very nice and descent. The homework is especially interesting and well designed.

By Nathan M

Jun 11, 2016

Great class; very informative! I was surprised to see that Brian mentioned the Central Limit Theorem; he definitely knows what he is talking about.

By 李佳童

Dec 01, 2015

Dividing a week's contents into modules and adding a brief introduction at the beginning of each module makes the course much more clear. Students can also know what programming assignments (swirl) they should do every week. I appreciate those changes in the new class.

By Son T H

Nov 06, 2017

Best course

By Marcelo A P

Aug 17, 2016

Need to improve the clarity of the lectures, but it´s a good course though.

By Lan D

Feb 17, 2016

I love your lectures so much, I understood much better than what it's used to be for statistics, it's funny as well, thank you.

By Samy S

Feb 12, 2016

Good overview of the fundamentals, including how to avoid some common statistical fallacies.

By Viditya T

Mar 26, 2018

Quite good content.

By Andrey V

Mar 10, 2017

Statistical inference is one of the most useful things in data analysis.

It was very interesting and useful course!!! Many thanks to authors!

By Dan K H

Jun 16, 2016

Excellent course well explained by Brian Caffo with both theory and practical examples!

By Luis C A

Sep 20, 2017

really good and awesome

By aditya n p

May 12, 2016

Awesome Course !!

By Yi-Yang L

May 09, 2017

Good

By Vinicio D S

Dec 22, 2017

Great course for getting an introduction into the Stats needed for Data Science