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

3,616 évaluations
700 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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651 - 667 sur 667 Avis pour Inférence statistique

par Chun-Fu W

Feb 13, 2017

Not explained well, had to take another statistical inference course. Not worth the money.

par Charly A

Oct 05, 2016

The instructor is about as convoluted as you can possibly get with his explanations.

par Seyed M

Aug 22, 2016

The slides are very difficult to follow. It could be better designed

par Christian

Jul 24, 2017

poor course material / slides makes it hard to follow...

par Cady

Jun 14, 2017

Too theoretical. Could not see practical applications.

par Bijan S

Feb 28, 2019

super boring instruction, instructor is like a robot!

par Stephen E

Jun 27, 2016

To be honest I don't think this is worth the money.

par Pranjal S

Feb 21, 2019

Too vague in explanation and building a story

par Laetitia D S

Aug 09, 2016

Very difficult to understand and follow

par Shikhar O

Aug 30, 2016

worst course of the specialization.

par Eric T

Feb 21, 2017

Important material, poorly taught.

par Katakam S T

Jan 29, 2019

no clarity in the explaination

par Pramod N

Jan 27, 2016

Cant understand whats going on

par Mukarram M

Jun 29, 2019

The worst teacher ever!

par Johannes H

Aug 05, 2016

Too much covered.

par paul d

Jul 14, 2018

bad lectures.

par Mekin L

Feb 23, 2018

huay mak mak