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Avis et commentaires pour d'étudiants pour Statistiques déductives par Université Duke

4.8
étoiles
1,713 évaluations
315 avis

À propos du cours

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data...

Meilleurs avis

ZC

Aug 24, 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

MN

Mar 01, 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

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276 - 300 sur 311 Avis pour Statistiques déductives

par Adara

Oct 17, 2017

It is a very nice course, I have learned a lot. However, it is convenient to take the previous one of the specialization, as they base some examples or R knowledge on it.

par Abiodun B

Mar 28, 2017

This course gave me the toughest time of my life. I did the course for 3 months, i failed project once but i thank God, i proved toughest by passing with 100%.

par Sergio E T

Jan 04, 2019

The inference function and hypotheses tests are really useful. Permutation tests need more explaining and examples; otherwise they should not be included.

par Aaron M

Nov 28, 2019

A good course for learning statistical inference, though I found that more than a week per module was required to really absorb the content.

par dumessi

Aug 13, 2019

It is a great course, while some underlying logics are not clearly explained. And the quiz has some unexplained context, which is confused.

par Lucía M F

Apr 23, 2020

It was a very interesting and useful course. To improve it a little bit, I would focus more on the use of R to do different analysis.

par Janusz P

Apr 29, 2018

I liked this course because it gives basic ideas how inferential statistics works, without going into mathematical details.

par Peter C

Nov 19, 2018

I thought this course did a great job of incorporating R code into the lecture and hope that continues in future courses.

par Richard M

Mar 08, 2019

Generally a great course, but would benefit from a better explanation at times of how to use R effectively.

par Markus K

Aug 18, 2017

Good videos, good book with exercises but many useful functions in R were not introduced (e.g. t.test()).

par kirran

Sep 06, 2018

More detailed answers on Quiz questions and some more explanation on R codes will help a lot

par Ghada S

Dec 12, 2019

I think it is a little bit difficult for someone who knows nothing about probability or R.

par mnavidad

Jun 15, 2018

This course is great learn a lot well explained, the professor is great!!!

par Robert F

Aug 08, 2016

Nice introduction to statistical inference concepts and techniques

par Shalabh S

Jun 01, 2017

Very nice coarse for learning methods of inferential statistics.

par Aravindan

Sep 03, 2018

Very well structured.Could focus on R programming a bit more!

par Adán

May 10, 2020

¡Es una pena que no se traten más contenidos! Está genial

par VEERARAGHAVAN V

Mar 06, 2018

Need to revisit few classes as it was little aggressive.

par Dgo D

Feb 22, 2017

Its a very good way to introduce to R language

par SAURAV P

Oct 29, 2016

good powerful insight into statistics. Thanks!

par Takahiro M

Mar 05, 2017

This is great course as Intro to Statistics

par Nathan H

Dec 26, 2017

I wish there was more exposure to R.

par José M C

Jan 04, 2017

Very useful tools for inference

par YUJI H

Dec 28, 2017

It is very difficult...

par Ananda R

Mar 13, 2017

excellent