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Avis et commentaires pour d'étudiants pour Inférence statistique par Université Johns-Hopkins

3,656 évaluations
718 avis

À propos du cours

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....

Meilleurs avis


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 .


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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526 - 550 sur 685 Avis pour Inférence statistique

par Vasudevan D

Jan 28, 2018

Too much concepts to learn and practice. Course material can be little more engaging and split accordingly.

par Maxim M

Dec 10, 2017

Very difficult lectures. You need a solid statistical background to keep up with the pace of the professor.

par Simon

Mar 02, 2017

The ideas and concepts explained here are really important but are explained/written in a bit messy manner.

par xuwei l

Sep 22, 2016

lectures notes is not details enough, had to google around other materials to grasp the courser work better

par Rezoanoor/CS/Rezoanoor R

Mar 13, 2020

It covers a lot of topics, good for that but submitting assignment via Swirl is extremely boring.

par Codrin K

Mar 05, 2018

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

par Alex F

Feb 12, 2018

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

par Lindsay S

Mar 02, 2017

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

par Gibson W

Feb 10, 2016

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

par Bernardo D F d S

May 20, 2016

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

par Chunyue Z

Jun 16, 2019

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

par Ali M

May 03, 2017

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

par Tomasz J

May 04, 2016

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

par Sergey

Jun 13, 2017

Unfortunately, the manner of presenting information desires the best.

par Sushil K

May 10, 2016

Steep Learning Curve. Swirl exercises are important for this course

par B S

Apr 25, 2018

Less good than expected. Explanations could be more clear.

par Pulkit K

May 26, 2018

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

par Tomasz S

Jan 18, 2020

Very fast course... Additional reading required.

par Thomas F

May 31, 2018

really bad review criteria for grading peers.

par chris

Jul 11, 2017

Heavy content to cover in such a short time

par Ram K P

Aug 03, 2018

Most lessons lack clarity. very evasive

par Lei M

Aug 23, 2017

The stuff is very high leveled for me.

par Tom C

Sep 16, 2018

Would be better if taught with Python

par Bharadwaj D

Apr 05, 2017

Learnt many new things. It was good.

par Koen V

Aug 11, 2019

Hard subject, hard explanations