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

4,136 évaluations
831 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

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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651 - 675 sur 799 Avis pour Inférence statistique

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.

par chris

11 juil. 2017

Heavy content to cover in such a short time

par Ram K P

3 août 2018

Most lessons lack clarity. very evasive

par Lei M

23 août 2017

The stuff is very high leveled for me.

par Tom C

15 sept. 2018

Would be better if taught with Python

par Bharadwaj D

5 avr. 2017

Learnt many new things. It was good.

par Koen V

11 août 2019

Hard subject, hard explanations

par Charbel L

7 mars 2019

Difficulty level is high...


2 mai 2020

Its good but not too good.

par Wassim K

5 juin 2017

Too mathematical for me

par Biju B

5 juin 2017

The lectures were Dry

par dipankar b

4 sept. 2017

Good, Productive

par David K

16 août 2017

a bit cursory

par Luv K

23 août 2020

Too complex

par Roberto L

11 nov. 2018

Too sparse.

par Ankush K

6 juil. 2017

Very basic.

par Santiago P G

1 août 2017

A hard one

par Suzhongdayi

11 juil. 2016

no passion

par Hani M

1 nov. 2016

A lot of the concepts in Stats Inf - although simple when you think about it and used pretty much every day - I felt were difficult to understand at first. Wikipedia and some other online sources, and youtube videos, were more helpful but I think the real issue lay in the teaching style. I won't knock Mr. Caffo like some of the others here have because at the end of the day everyone learns differently. What works for some might not work for others and unfortunately his style did not suit my learning requirements.

My rating is purely based on the content which I think can be simplified by giving more visual examples. I am rating this after taking the 'Regression Models' course and in that course it is MUCH easier because he gives "real time" and visual examples of what, eg Residuals, mean or represent. Just that alone made a huge difference and it then helps me focus on how to write the R code rather than trying to understand the math. Hope this helps!

par Vincenc P

11 févr. 2016

I am left feeling this course needs work. I don't know if it's the pain of switching to the new platform or what, but the total lack of any support from the TA/instructor team is frustrating. Add to that the fact that Brian skips from slide to slide very quickly often not providing adequate explanations and you'll be re-watching the videos many times over.

Several of the videos have blatant errors in them, like the fast that the fourth video of a week also contains the entire third video... again.

Such things should not have passed a half decent QA test.

More than anything this specialization should not be marketed as "no previous experience needed". You need to know some statistics. And by some, I mean do the whole thing on Khan Academy first.