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Opiniones y comentarios de aprendices correspondientes a Inferencia estadística por parte de Universidad Johns Hopkins

3,744 calificaciones
746 revisiones

Acerca del Curso

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....

Principales revisiones


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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426 - 450 de 714 revisiones para Inferencia estadística

por Michael H

Jun 02, 2018

Tough, but good information presented in a way to capitalize on R for doing statistical analysis

por Manh H T

Jan 14, 2017

The course is useful and essential not only for those studying statistics but machine learning

por vidhi j

Jan 26, 2020

It is pretty difficult and needs research and homework to be done from the learner's side

por Luong M Q

Jul 27, 2017

It was hard to get into the idea of some statistics aspects, but it is helpful in general

por Frank I

Aug 29, 2017

A very good statistcal background course, taught in a very accesible but thourough way.

por Melanie B

Apr 02, 2018

Access to the keys to the quiz was helpful for correcting mistakes and misconceptions.


Jul 24, 2017

ok. It was really an ample amount of knowledge domain which I inculcated from this mod

por Zoran K

Apr 20, 2017

Statistics was relatively new to me, so it was a steep learning; Overall I liked it.

por Paul M

Dec 30, 2016

Great Course. Material much more challenging than courses in the program to date.

por Sandhya A

May 23, 2018

I learned a lot, but found it relatively difficult as compared to other courses

por Francisco G A

Jun 26, 2016

good curse, but it's hard by short time to study all lessons and practice it.

por Sherifat A

Sep 12, 2018

Took a lot of time and re watching the videos but the knowledge was worth it

por Artem V

Dec 15, 2016

It's not the math that is hard, it's the phrasing, vocabulary and semantics.

por Shubham G

Dec 16, 2016

Very informative lecture and Brian explained concepts pretty well. Thanks..

por Falko K C

Aug 07, 2016

Great course, could use some review though. Still give it a big thumbs up!

por xuanru s

Nov 28, 2016


por Meredith C H

Aug 26, 2018

Taught a lot of useful skills, but lectures were often hard to follow

por Rohit D

Mar 21, 2017

Nice course, but need more detailed one for those new to statistics.

por Jack F

Mar 28, 2020

Very thorough in covering not only theory, but application as well.

por Gabriel G

Apr 17, 2019

Very good course, but requires a basic understanding of statistics.

por antonio q

Mar 08, 2018

very well done, thanks a lot for everything, I did learn a lot,

por Deleted A

Nov 13, 2016

a basic course of inference but i think perfecto for this mooc

por Richard D

Jul 14, 2017

Fantastic, but quite a lot of material packed into 4 weeks.

por Manojkumar P

Oct 24, 2016

It is nice course!

Amazingly challenging, thought provoking.

por Daniiar B

Sep 10, 2018

The content is good, but the teaching is a little tedious