Chevron Left
Back to Statistical Inference

Learner Reviews & Feedback for Statistical Inference by Johns Hopkins University

4.2
stars
4,427 ratings

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 25, 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 .

RI

Sep 24, 2020

the teachers were awesome in this course. I liked this course a lot.Understood it properly.Thanks to all the beloved teachers and mentors who toiled hard to make these course easy to handle.Gracious!

Filter by:

701 - 725 of 869 Reviews for Statistical Inference

By Codrin K

Mar 5, 2018

Too bad it all starts from mathematical theorey; I would prefer a problem based approach.

By Alex F

Feb 12, 2018

Very detailed and a little painful :) but I am sure it will be useful information

By Lindsay S

Mar 2, 2017

These are complex topics, and just the quick overview doesn't fully explain them.

By Nicolás H

Oct 11, 2020

Me hubiera gustado tener más detalle de algunos conceptos clave de estadística.

By Gibson W

Feb 9, 2016

Not one a statistics newbie should take, had to take it twice just to grasp 80%

By Bernardo D

May 20, 2016

Content runs a bit fast but good course for stat inference with R focus.

By 郑淳玥

Jun 15, 2019

The materials are not so clear to someone who's not familiar with stat.

By Ali M

May 3, 2017

Concepts weren't explained properly. The instructor was going too fast.

By Tomasz J

May 4, 2016

It's quite involved, fast and not explained thoroughly in some places.

By Sergey

Jun 13, 2017

Unfortunately, the manner of presenting information desires the best.

By Sushil K

May 10, 2016

Steep Learning Curve. Swirl exercises are important for this course

By B S

Apr 25, 2018

Less good than expected. Explanations could be more clear.

By pulkit k

May 26, 2018

I don't like the example and the explanation at all.

By Jim M

Jun 7, 2020

Great material, but could be better organized.

By Thomas F

May 30, 2018

really bad review criteria for grading peers.

By chris

Jul 11, 2017

Heavy content to cover in such a short time

By Ram K P

Aug 3, 2018

Most lessons lack clarity. very evasive

By Lei M

Aug 23, 2017

The stuff is very high leveled for me.

By Tom C

Sep 15, 2018

Would be better if taught with Python

By Bharadwaj D

Apr 5, 2017

Learnt many new things. It was good.

By Koen V

Aug 11, 2019

Hard subject, hard explanations

By Charbel L

Mar 7, 2019

Difficulty level is high...

By KUNAL J

May 2, 2020

Its good but not too good.

By Wassim K

Jun 5, 2017

Too mathematical for me

By Biju B

Jun 5, 2017

The lectures were Dry