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Вернуться к Improving Your Statistical Questions

Отзывы учащихся о курсе Improving Your Statistical Questions от партнера Технический университет Эйндховена

Оценки: 94
Рецензии: 21

О курсе

This course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions. In practical hands on assignments you will learn techniques and tools that can be immediately implemented in your own research, such as thinking about the smallest effect size you are interested in, justifying your sample size, evaluate findings in the literature while keeping publication bias into account, performing a meta-analysis, and making your analyses computationally reproducible. If you have the time, it is recommended that you complete my course 'Improving Your Statistical Inferences' before enrolling in this course, although this course is completely self-contained....

Лучшие рецензии


11 мая 2020 г.

Fantastic state-of-the-art and practical knowledge. It is very useful for researchers at any stage of the scientific career. Thank you, Daniel.


2 янв. 2020 г.

Excellent! Would like only one addition, and that's a more extensive exercise on simulating data with general linear models

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1–21 из 21 отзывов о курсе Improving Your Statistical Questions

автор: Nora P H L

5 февр. 2020 г.

Very relevant course, specially if you currently work, or you are interested in working, as a researcher. One of the most important abilities for the scientific work is to be able to produce relevant, or at least informative studies; that's the whole point of science, and it's very sad that most of us (researchers) don't fully understand how to correctly assess/conduct research, and the importance of it. This course will definitely help you realize and construct the statistical thinking necessary to improve scientific practices.

автор: Enis -

27 июня 2020 г.

One of the best online courses I have ever seen.

автор: Stephen S

11 июля 2020 г.

I believe that this second course from Daniel Lakens is one of the "must take" classes offered via Coursera. The structure and coursework are some of the best that I've seen yet. The quality of the course was truly worth a five-star rating.

автор: Luca F

21 нояб. 2019 г.

Splendid as everything that is produced (either recorded or written) by Daniel Lakens!

The course forces you to stop and think, instead of simply doing things.

And this stop-and-think part, often overlooked, is exactly what distinguish someone who gives real value to his team and projects from one who just produces statistical outputs.

Brilliant, simply brilliant and enlightening.

автор: Ryan F

1 нояб. 2019 г.

Absolutely phenomenal course. Dr. Lakens does an excellent job of making complex topics more approachable, and of explaining concepts using alternative approaches. I've now taken both of his MOOCs and have thoroughly enjoyed each one. As a side bonus, the r-based assignments are excellent for novice r users looking to build their skill-set.

автор: Carlos G S

16 мар. 2020 г.

I liked this course as much as the previous MOOC from Lakens. The introduction to metanalisis and SESOI are my preferred modules. The only problem is some modules are similar to previous MOOC but slightly different, and sometimes it is confussing. Daniel Lakens is the best teacher of statistics I have ever met. Thank you!

автор: András H

12 мая 2020 г.

Fantastic state-of-the-art and practical knowledge. It is very useful for researchers at any stage of the scientific career. Thank you, Daniel.

автор: Sam W

1 янв. 2020 г.

Cracking - very informative, nice mixture of modes of learning, and engaging

автор: Larry P

30 окт. 2019 г.

Daniel's second course as good as the first. He does a nice job!!

автор: Alex R

24 нояб. 2019 г.

Lots of really interesting material presented in a great way. The reading and lectures inspired me to read more and clarified questions that have long been on the edges of my understanding of science.

The home works were a little rote but I think that helps make the calculations clearly within our grasps. The only frustrating thing was the course depends on a handful of libraries which were tough for me to install. I eye-balled some graphs that were included with the home works and had a to think a bit more about some questions that were generally "change x to y and rerun, what is the value of z?"

автор: Lee V

17 янв. 2022 г.

A very good course that's probably best taken after Daniel Lakens' other Coursera MOOC on statistics - this one's tougher. As well as talking through the important issues in experimental design that provide the potential for valid statistical solutions, the course provides links to a range of on-line tools to help. The sections on philosophy of science also help in this respect as they shed a light on the kinds of questions experimenters ask.

автор: Juli T

8 нояб. 2019 г.

This course teaches you the things about statistics that no one tells you about at uni - even though they are extremely important. The MOOC has a nice pace for people with a basic foundation in statistics and provides enough time and exercises to allow for the concepts to sink in. The R scripts are a huge bonus.

автор: Jana H

29 нояб. 2019 г.

Absolutely great. I immensely enjoyed the previous MOOC by Dr. Lakens and this one offered the option to recapitulate and enhance my understanding of more complex concepts. I am recommending all my fellow researchers to take his coursers, they changed the way I do my research and view science itself.

автор: Hande S

4 дек. 2019 г.

I recommend this course to everyone who wants to improve their grasp of statistics. The course involves content that is timely and relevant within an easy-to-digest form and amount.

автор: MilFi

18 февр. 2020 г.

Dr. Lakens passes ET test with very tiny SESOI. As usual. I was suitable only for two tailed NHST without any direction of effect. Put another way: "anything goes" :o)

автор: Shambhavi C

3 янв. 2020 г.

Excellent! Would like only one addition, and that's a more extensive exercise on simulating data with general linear models

автор: Marcin M

17 мар. 2021 г.

Well connected and inspired course. Thank you very much for shared information and knowledge.

автор: Arnaud s

24 нояб. 2019 г.

Great course that will definitely be useful in my academic career (and more than that!)

автор: TIAGO B L

7 мар. 2022 г.

G​reat course! Was a pleasure to take it. Thanks, Professor Lakens!

автор: Aditya A

26 июля 2021 г.

Exceptionally important course

автор: Stephen A

17 авг. 2020 г.

Really enjoyed