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

4.2
étoiles
4,049 évaluations
804 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

JA

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 .

MI

Sep 25, 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!

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426 - 450 sur 771 Avis pour Inférence statistique

par Thakur G S

Dec 16, 2016

the course provides the necessary information and practice assignments to build a grasp of the topic. It seems a little fast paced and people from non-statistics background may find it a bit difficult.

par Mauro S d S

Mar 05, 2017

For starters, it will demand a lot of out of class studies. It took me three months to go through the basics in Khan Academy before attempting it - and after that it was straight forward.

par Carlos

Feb 23, 2016

This was probably the most difficult and challenging course . Had to pull out my old stats books to remember most of it. Using R to do what we used to do with TI-83's was great!

par Andy T

May 11, 2020

This course explores many key statistical concepts, however you are expected to extend your learning beyond the course in order to fill in any foundational gaps in statistics.

par Abishek S

Apr 19, 2020

This course is slightly difficult, and to attempt the quizzes and the project, the student must do some more external research...

Otherwise, great introduction to statistics!

par Aashaya M

Feb 25, 2016

This is course is well written , the Lecturer notes are very handy and Swirl Lessons give us Hands on Experience in Practical Implementation.

Thanks for the instructors

par Rodrigo A d S R

Aug 20, 2018

Really good course, a bit difficult since it jumps right into technical language, but it gives you a good solid base for the following courses in the specialization

par Vitalii S

Jul 04, 2017

I think it would be better to send solution in .html and not .pdf, because you need to install 3rd party software. In other aspects course is very cool. Thank you.

par Liam P B

Jun 01, 2020

Good introduction to probability and statistics. I think it moves too quickly for absolute beginners but its probably a fine compromise between depth and breadth.

par Jordan G

Feb 14, 2016

I wish there was more R programming focus. I feel like there was a lot of theory, and then a blanket "t.test will cover this" treatment of implementation in R.

par Piotr K

Oct 23, 2016

Sometimes videos was difficult to understand. I needed to watch most of lectures twice. On other hand it was worth doing and I've learned basic statistics.

par Connor G

Aug 22, 2017

I learned a lot from the lectures and felt that the quizzes were adequately challenging, but I was expecting to do more with the peer-graded assignments.

par Max M

Oct 31, 2017

Maybe a little fast paced for someone seeing these topics for the first time, but overall great content that I think will be a great help in my career.

par Veronica

Nov 04, 2018

I've tried to learn statistics for so many time and it is never less painful. This course is a good overview and exercises/quiz always help the most!

par David J G

Feb 04, 2016

I think you can get a lot from this course, but you have to deploy a reasonable amount of time to find for yourself more in depth concepts elsewhere

par Antonio F

Jun 25, 2016

It is a good course, well taught. A full comprehension of the subjects however needs more work and research than what is needed to pass the course.

par Nik M N N G

Mar 27, 2019

Overall, this is a good course to learn statistics. The quality of the video could have been better but the stuff presented is still clear to me.

par Tommy S

Mar 08, 2019

I really enjoyed the course and material. Very good explanations in the video and the book does a good job of explaining what the videos go over.

par Jay S

Jul 29, 2016

A foundation course for data scientists! Basic statistics from University of Amsterdam on Coursera would be nice pre-requisite to this one !

par Ramiro A

Jun 28, 2016

Content was Great, difficult to understand some times. I had to review more sources to get the clearer idea.

Totally enjoyed the challenge.

par Robert W S

Mar 17, 2016

Good refresher course. It'd be a little steep of a learning curve for someone new to hypothesis testing/confidence intervals in four weeks.

par Connor B

Aug 28, 2019

The course project was the most beneficial for me because I got to work with real data it helped me understand the concepts much better.

par Vincent G

Aug 14, 2017

Very good material. I only wish the examples could be more varied to include some "business" examples as opposed to mainly bio med ones.

par Juan B M V

Sep 25, 2016

Touches all the key concepts of statisticas inference. A bit challenging, even more if you don't have previous knowledge of statistics.

par Harsh G

May 29, 2020

Overall a great course to learn and understand, few concepts weren't explained properly and I faced difficulties in adapting to those.