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Improving your statistical inferences(으)로 돌아가기

아이트호벤 공과 대학의 Improving your statistical inferences 학습자 리뷰 및 피드백

4.9
별점
715개의 평가
236개의 리뷰

강좌 소개

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"...

최상위 리뷰

MS

2021년 5월 13일

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

2021년 7월 10일

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.

필터링 기준:

Improving your statistical inferences의 235개 리뷰 중 226~235

교육 기관: Max R

2019년 11월 29일

It was nice. I initially hoped the course would have made some technical details intuitively graspable, but it was fine as it is.

교육 기관: Mage I

2018년 6월 20일

The course was very useful, I enjoyed Daniel's advice. However, I wasn't able to make R work, so I couldn't do the exams.

교육 기관: Sanne D

2018년 5월 27일

Questions are sometimes hard to understand if you are not a native speaker of the English language

교육 기관: Leanne C

2019년 1월 3일

Very informative course, well taught and with lots of useful practice built into the assignments.

교육 기관: Wong J K

2020년 11월 27일

Excellent course to better understand statistics

교육 기관: Elías E

2019년 7월 29일

Very informative.

교육 기관: Yao Y

2016년 11월 27일

The video is ok, but it lacks a lot of details in calculation. The assignment is very confusing because some questions refer to some 'previous' statement while fail to clarify which is related.

교육 기관: Aicha M A N

2020년 11월 12일

Good afternoon, I have finished my course since 5th November and I didn't get my certificate yet.

교육 기관: Emmanuel k A

2019년 6월 21일

I started just today and I'm beginning to love the course

교육 기관: Dashakol

2018년 9월 21일

I dropped the course at Lecture 1.2 when it was supposed to really teach me what is p-value but it failed. A 20 min video without telling much about p-value and also adding more confusion and unanswered questions at the end. Like what is p-value distribution?

I expected to receive a decent step by step tutorial on statistics starting from basics but it was just another convoluted stuff on statistics.