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Voltar para Estatística Inferencial

Comentários e feedback de alunos de Estatística Inferencial da instituição Universidade Duke

4.8
estrelas
2,421 classificações

Sobre o curso

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...

Melhores avaliações

MN

28 de fev de 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!

ZC

23 de ago de 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!!!

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376 — 400 de 434 Avaliações para o Estatística Inferencial

por rob p

27 de ago de 2018

This course seemed unbalanced compared to some of the other courses and was very work-heavy. I felt it could have, or maybe should have been broken up into two courses, or that other courses should be longer.

por Georgios P

8 de jan de 2021

The final project does not help, for example someone used discrete data 1,2,3,4,5 .... ,40 to compute a p.value as if it was normal. It is too general and does not fill the purpose of the course.

por Koo

8 de nov de 2020

I love this course. But I have a little bit hard for using the R program. If there is more instruction about using the R program, this course would be a lower hurdle for users likes me.

por Amit C

18 de fev de 2019

The course is very well explained I had to refer other materials for ANOVA technique to understand it better hence that part can be either improved OR more reference material be provided

por Zhang Q

23 de nov de 2018

Very useful course about statistics. May need some fundamental understanding of statistics before, but through the clear explanation and examples, I've learnt a lot from this course

por greena m s

30 de jul de 2020

This is a wonderfully curated course if u follow the readings and practise suggestions. But the main issue is the R programming. It needs better practise than suggested readings.

por MEKALA S N

10 de jun de 2020

Very good course on basic understanding of inferential statistics. Instructor was very clear in delivering the content. The lab work is very helpful in developing R knowledge.

por Paul N

17 de ago de 2016

The teaching is good, the course is a little heavy and a lot to take in in the later weeks. But, as a further grounding for statistics and R, I would very much recommend it.

por Adara

17 de out de 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.

por Stefano D V

17 de jun de 2020

Without a background in confidence intervals and hypothesis testing, I think that it would be very difficoult to understand these concepts in those few videos.

por Abiodun B

27 de mar de 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%.

por Sergio E

4 de jan de 2019

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

por Aaron M

28 de nov de 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.

por dumessi

13 de ago de 2019

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

por Lucia M

23 de abr de 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.

por Janusz P

29 de abr de 2018

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

por Peter C

18 de nov de 2018

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

por Rohit D W

14 de ago de 2020

An Introductory course with a lot of examples and a project at the end to furnish your concepts and knowledge.

por Richard M

8 de mar de 2019

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

por Markus K

18 de ago de 2017

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

por Kirran R M R

6 de set de 2018

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

por Mikhail I

16 de jul de 2020

good course overall. Would love to see more math exercises rather than wording of problems.

por Ghada S

12 de dez de 2019

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

por mnavidad

14 de jun de 2018

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

por Robert F

8 de ago de 2016

Nice introduction to statistical inference concepts and techniques