Chevron Left
Retour à Inférence statistique

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

4,350 évaluations

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


25 oct. 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 .


24 sept. 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!

Filtrer par :

826 - 850 sur 850 Avis pour Inférence statistique

par Imogen S

31 oct. 2017

Not a very well-structured subject. Need to make clearer demonstrations and explanations on the theories.

par sateesh

3 mai 2016

The course is very difficult to comprehend..Moreover the examplanations given ar not concise and brief..

par Ravi t B

7 mai 2017

No proper meaningful explanation for the logic derived, especially in Probability, the core of stats.

par Tony W

13 févr. 2017

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

par Charly A

5 oct. 2016

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

par Danish S

12 juil. 2021

Bad explanation and lecturer seems like in a rush and reading from his notes

par Seyed M

22 août 2016

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

par Aarohi V

3 févr. 2021

At last no proper instruction given about how to complete the task.

par Christian

24 juil. 2017

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

par Cady

13 juin 2017

Too theoretical. Could not see practical applications.

par Bijan S

28 févr. 2019

super boring instruction, instructor is like a robot!

par Stephen E

27 juin 2016

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

par Pranjal S

21 févr. 2019

Too vague in explanation and building a story

par Laetitia D S

9 août 2016

Very difficult to understand and follow

par Shikhar O

30 août 2016

worst course of the specialization.

par Eric T

21 févr. 2017

Important material, poorly taught.

par Katakam S T

29 janv. 2019

no clarity in the explaination

par Pramod N

26 janv. 2016

Cant understand whats going on

par Sai S

9 févr. 2022

no peer submissions available

par Mukarram M

29 juin 2019

The worst teacher ever!

par youssef m

19 janv. 2022


par Johannes H

5 août 2016

Too much covered.

par Paul D

14 juil. 2018

bad lectures.

par Mekin L

23 févr. 2018

huay mak mak

par Milad G A

9 nov. 2020

i dont like