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

4,387 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!

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226 - 250 sur 856 Avis pour Inférence statistique

par Illich M

15 juin 2017

This is a tough course! I had to take it multiple times to understand it.

par Jorge B S

3 juin 2019

Very nice introductory course to statistical inference concepts using R.

par Sanjeev K

2 avr. 2018

A great course for the beginner who are new to the field of Data Science

par Huey Y T

21 mars 2017

I enjoyed the lectures. The lecturer was very clear on the explanations.

par Bopeng Z

8 juin 2017

Very useful and thorough review of statistics. Invaluable in practice.

par Simeon E

20 févr. 2017

Not so easy, but extremely interesting. Highly recommended to anyone.

par Sebastian R

19 sept. 2017

Great intro to statistical inference. Also, the materials are awesome

par Raunak S

1 nov. 2018

nice course before digging deeper into Data Science advanced topics.

par Karthik R

7 août 2017

Good Course, but I think you need to have some Statistics background

par Diego N

26 mars 2017

Excellent course to get up to speed on important statistics concepts

par sujatabosesinha

7 mars 2017

Good course. Quite thorough. Nice blend of R programming and theory.

par Bojan B

14 oct. 2018

Great course with great materials. Easy to understand and to learn.

par Maxim K

2 févr. 2016

I like lesson, teacher on video don't quickly and easily explained.

par Sally L

13 déc. 2016

Very Informative. Have to devote quite a bit of time to it though.

par Ewa W

3 nov. 2016

Great course, very challenging . Well presented , great material .

par Daniel B

15 mars 2016

This course gives a really good overview in statistical Inference.

par Wojciech O

12 janv. 2016

Very good reminder of mathematical statics which I had on studies.

par Xiaofeng H

30 oct. 2021

It's not easy to understand initially. Swirl is very beneficial.

par Michael O D

19 nov. 2019

Excellent and stimulating course, swirl tutorials very effective.

par Owais M

15 nov. 2017

Nice course! focussing mostly on hypothesis testing and p-values.

par Christian B

11 mars 2017

Content is very good overall. Presentation could be more engaging

par Umang T

8 sept. 2020

Course is very good and very productive knowledge provided in it

par THI A A

31 juil. 2020

This course refresh my memory for statistic and prepare me for M

par Arushi A

5 déc. 2017

Amazing course content and assignments for practical application

par Larry G

7 févr. 2017

This course should be in 3-4 courses.

Maybe a full specialization