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Отзывы учащихся о курсе Improving your statistical inferences от партнера Технический университет Эйндховена

4.9
звезд
Оценки: 703
Рецензии: 234

О курсе

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis. Finally, we will talk about how to do philosophy of science, theory construction, and cumulative science, including how to perform replication studies, why and how to pre-register your experiment, and how to share your results following Open Science principles. In practical, hands on assignments, you will learn how to simulate t-tests to learn which p-values you can expect, calculate likelihood ratio's and get an introduction the binomial Bayesian statistics, and learn about the positive predictive value which expresses the probability published research findings are true. We will experience the problems with optional stopping and learn how to prevent these problems by using sequential analyses. You will calculate effect sizes, see how confidence intervals work through simulations, and practice doing a-priori power analyses. Finally, you will learn how to examine whether the null hypothesis is true using equivalence testing and Bayesian statistics, and how to pre-register a study, and share your data on the Open Science Framework. All videos now have Chinese subtitles. More than 30.000 learners have enrolled so far! If you enjoyed this course, I can recommend following it up with me new course "Improving Your Statistical Questions"...

Лучшие рецензии

MS
13 мая 2021 г.

Eye opening course. My first introduction to some of the issues surrounding p-values as well as how to better utilize them and what they truly represent. My first introduction to effect sizes as well.

VM
10 июля 2021 г.

Solid course which taught me how to interpret p-values in a variety of contexts and taught me to not just to consider but (systematic and practical) ways of how to correct for publication bias.

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101–125 из 232 отзывов о курсе Improving your statistical inferences

автор: Oleksandr H

25 нояб. 2016 г.

Some courses are useful in the short run while others can challenge your way of thinking for the rest of your professional life. This course is the latter!

автор: Wilte Z

23 окт. 2016 г.

Clear explanations of the concepts of statistics, without too much emphasis on the formulas. With handy references to online tools, like power calculators.

автор: Iván Z A

15 февр. 2017 г.

Wonderful course: very interesting, and very well explained. Also, the teacher is a very kind and helpful person (at least in Twitter ;-P). Thanks Daniël.

автор: Ernesto M

30 июля 2018 г.

Excellent course that changed my views on interpreting p-values, confidence intervals, etc. and will surely make my statistical inferences much better.

автор: Muhammad T S

8 нояб. 2017 г.

This is a very powerful course. Simple content but with lots of depth and newer perspective on statistical testing. Learned a lot. Highly recommended.

автор: Moos L

6 нояб. 2016 г.

Excellent, may I say indispensable course for every social scientist out there to improve their statistical skills. Very coherent and comprehensive!

автор: Eloy A O

23 июня 2020 г.

Very complete course, I learned a lot with the videos and assignments. Professor Daniel explains very well too . I recommend it completely.

Thanks!

автор: Nicholas

28 апр. 2019 г.

Fantastic course on inference, difference between frequentist and Bayesian concepts like p-values, confidence and credible intervals, and validity.

автор: Sanjeev P

13 нояб. 2016 г.

Fantastic, enjoyable, entertaining with a dash of humor. Highly recommended for non-statisticians interested in improving their grasp of the field.

автор: Sebastian U

26 мар. 2018 г.

The course gave me useful insight into interpreting and handling statistical parameters. Information and methods were well balanced. Thank you.

автор: Tyron J

8 янв. 2022 г.

Really interesting course that dives into how to do proper statistics. Professor Lakens is one of the best instructors I've seen on Coursera.

автор: Ted T

29 мар. 2020 г.

Top quality course. Learnt a lot thanks to the very helpful and clear teaching. Put the equivalent course at my actual university to shame.

автор: Michael E

25 июня 2017 г.

Thank you. This course represents a great deal of important work for me to continue to revisit and incorporate in my efforts moving forward.

автор: Ляшенко І В

6 авг. 2020 г.

This was an incredibly fresh eye-opener course with a load of practical invaluable skills for my professional activity! Highly recommended!

автор: Kathryn S

9 дек. 2017 г.

I absolutely loved Prof Lakens' clarity! The effort he put into making the material and the assignments easy to understand is astounding.

автор: Jingbo H

12 июня 2018 г.

very good course! The teaching style is good and the assignment in R is very helpful for me to understand the main ideas of this course.

автор: Mathew L

4 июня 2017 г.

One of the best courses I've ever done. Fundamentally practical. I learned a great deal and challenged a lot of my implicit assumptions.

автор: Jana H

4 мар. 2017 г.

Wonderful course! It was really well-conceived and I learned a lot. Would definitely recommend it to everyone interested in statistics!

автор: Romain R

10 янв. 2019 г.

Great overview of statistics and philosophy of science. Now I know what to tell my students when they ask me about p-values. At last !

автор: Munzar A S

10 апр. 2020 г.

Fabulous course! Points out a lot of the nonsense going on in psychological research, how we can spot it, and how we can do better!

автор: marcus n

4 февр. 2017 г.

Great high level overview of intermediate applied statistics. The instructors presentation skills and pace are very good as well.

автор: Maxim P

22 мар. 2020 г.

Such a wonderful course, I really enjoyed the walkthrough. Also, I'd like to note the perfect English language of the lecturer.

автор: Dennis H

4 дек. 2018 г.

excellent refresher and expansion on frequentists stats (interpretation) and nice intro to bayesian stats. highly recommended.

автор: Katia D

11 февр. 2018 г.

Great course! Although I was struggling with lecture 2 (Bayesian Statistics)––It was very mathsy and a bit difficult to follow.

автор: Ester N

24 янв. 2022 г.

L​earned a lot during this course and it left me with a lot of challenges with planning my own research. I am very grateful.