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

3,898 évaluations
774 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 - 675 sur 741 Avis pour Inférence statistique

par CW

Jun 14, 2016

Very poor instruction and organization of topics, very poor explanation of core concepts. I learned more from reading other sources while taking the class than I did from the lectures.

par Yohan A H

Jul 10, 2019

The topics are very interesting and there is no dude that the teacher knows wath he is teaching, even though I think it can be better with more grapics splanations and less formulas.

par marie s

Jul 05, 2017

A lot of the course were not explained in a way that made it easy to understand for a neophyte. I had to go re-watch most of the lessons on khan academy to understand the principles.

par Esha D

Feb 11, 2016

professors caffo and leek go way too fast and are completely monotonous. the examples they use assume we know basic stats when likely most of us are a bit rusty.

par Andaru

Feb 06, 2016

The class needs to be more accessible especially for non statisticians, I learned more from khan academy which got me through this class than the class itself

par Peggy C

Feb 01, 2016

This is the worst course so far. This should be a 2 month course or the course descritpion should be changed to make sure you have some statistics knowledge.

par Jose P

Mar 21, 2018

Course needs more hands on example on all statistical inference tools - trying to disconnect from the daily routine and dive right into stats was difficult.

par Nelson G C G

Mar 29, 2016

There are better courses on the subject on coursera and other platforms. It worth it pursuing it if you are interested in joining the capstone project.

par Romain F

Jun 09, 2016

Seemed like a "ghost" course, issues reported with the swirl package, duplicate questions in the final assessment, where is the instructor ?

par Shikha B

May 10, 2016

Teaching material is fine. The Professor's explanation is monotonic and he uses textual definitions rather than simple explanations

par Emanuel A F d S

Jul 23, 2017

The course lectures are very confusing. I had to read a statistics book to clarify some of the concepts.

par Mario R

Jan 30, 2016

The instructor is not very good when compared to the others that are involved in this specialization.

par ooi s m

Jun 13, 2017

Lots of formula without detail explanation, not recommended for people without statistics knowledge.

par Fabian H

Jun 15, 2016

Concepts are very hard to understand, even with some background knowledge in statistics.

par Chengde W

Jun 24, 2017

He is just reading the slides. I'd prefer to read a book rather than watch the videos.

par Gareth S

Jun 14, 2017

Assumed a level of knowledge of stats already. Found it went too complex too quickly.

par Haolei F

Apr 15, 2016

Not beginner friendly, might be good as a refresher for grad students

par Daniel R

May 14, 2016

This course was more like a glossary. Not quite good but practical

par Colin B

Feb 02, 2019

Teacher is a bit erratic. It makes the course hard to follow.

par Peter H

May 17, 2016

Poor concepts exposition with a bad teaching method.

par Chen X

Mar 04, 2018

This class is not very well explained.

par Hariharan D

Aug 12, 2017

Pedagogy needs to be improved.

par Zaid M M

Dec 15, 2018

Could be better ...

par Anamaria A

Feb 28, 2017

Too much, too soon.

par Nicolas C

Aug 17, 2017

For beginners.