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

4.2
étoiles
3,898 évaluations
774 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 .

AP

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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576 - 600 sur 741 Avis pour Inférence statistique

par Hernan S

Apr 16, 2016

The subject is interesting, but the explanations are a little confusing. May need more diverse real-life examples to relate.

par Masahiro H

Mar 27, 2016

it gives an idea of how one is prepared to ingress to Data Science. I

see that I need to review it more carefully later on.

par Stavros S

Nov 21, 2019

Weeks 3 and 4 should have been split into 2 extra weeks to explain the concepts deeper and also have more exercises

par Marcus H Y T

Jun 02, 2019

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

par Maria C I S

May 02, 2019

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

par Joe F

Nov 27, 2016

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

par Vasudevan D

Jan 28, 2018

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

par Maxim M

Dec 10, 2017

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

par Simon

Mar 02, 2017

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

par xuwei l

Sep 22, 2016

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

par Rezoanoor/CS/Rezoanoor R

Mar 13, 2020

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

par manuel s g

Jul 05, 2020

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

par Codrin K

Mar 05, 2018

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

par Alex F

Feb 12, 2018

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

par Lindsay S

Mar 02, 2017

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

par Gibson W

Feb 10, 2016

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

par Bernardo D F d S

May 20, 2016

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

par Chunyue Z

Jun 16, 2019

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

par Ali M

May 03, 2017

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

par Tomasz J

May 04, 2016

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

par Sergey

Jun 13, 2017

Unfortunately, the manner of presenting information desires the best.

par Sushil K

May 10, 2016

Steep Learning Curve. Swirl exercises are important for this course

par B S

Apr 25, 2018

Less good than expected. Explanations could be more clear.

par Pulkit K

May 26, 2018

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

par Jim M

Jun 07, 2020

Great material, but could be better organized.