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

4.2
étoiles
4,341 évaluations
878 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

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 .

MI

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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676 - 700 sur 846 Avis pour Inférence statistique

par Marcus H Y T

1 juin 2019

Concepts are not well explained and slides are not well prepared. Last few topics are too brief to be useful.

par Aia S

1 mai 2019

3 stars because a total beginner would not have been able to follow these lessons without a lot of rewinding.

par Joe F

27 nov. 2016

Materials need to be updated - there are way too many inconsistencies between videos, exercises, and slides.

par Vasudevan D

28 janv. 2018

Too much concepts to learn and practice. Course material can be little more engaging and split accordingly.

par Maxim M

10 déc. 2017

Very difficult lectures. You need a solid statistical background to keep up with the pace of the professor.

par Deleted A

2 mars 2017

The ideas and concepts explained here are really important but are explained/written in a bit messy manner.

par xuwei. l

22 sept. 2016

lectures notes is not details enough, had to google around other materials to grasp the courser work better

par Muhammad M A S

11 janv. 2021

It's very important and very helpful, but it needs to be of more time/low speed to be perfectly absorbed.

par Rezoanoor/CS/Rezoanoor R

13 mars 2020

It covers a lot of topics, good for that but submitting assignment via Swirl is extremely boring.

par manuel s g

5 juil. 2020

This is module where I have learn less. Instructor also was not dynamic as previous ones.

par Codrin K

5 mars 2018

Too bad it all starts from mathematical theorey; I would prefer a problem based approach.

par Alex F

12 févr. 2018

Very detailed and a little painful :) but I am sure it will be useful information

par Lindsay S

2 mars 2017

These are complex topics, and just the quick overview doesn't fully explain them.

par Nicolás H

11 oct. 2020

Me hubiera gustado tener más detalle de algunos conceptos clave de estadística.

par Gibson W

9 févr. 2016

Not one a statistics newbie should take, had to take it twice just to grasp 80%

par Bernardo D

20 mai 2016

Content runs a bit fast but good course for stat inference with R focus.

par 郑淳玥

15 juin 2019

The materials are not so clear to someone who's not familiar with stat.

par Ali M

3 mai 2017

Concepts weren't explained properly. The instructor was going too fast.

par Tomasz J

4 mai 2016

It's quite involved, fast and not explained thoroughly in some places.

par Sergey

13 juin 2017

Unfortunately, the manner of presenting information desires the best.

par Sushil K

10 mai 2016

Steep Learning Curve. Swirl exercises are important for this course

par B S

25 avr. 2018

Less good than expected. Explanations could be more clear.

par pulkit k

26 mai 2018

I don't like the example and the explanation at all.

par Jim M

7 juin 2020

Great material, but could be better organized.

par Thomas F

30 mai 2018

really bad review criteria for grading peers.