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学生对 埃因霍温科技大学 提供的 Improving your statistical inferences 的评价和反馈

4.9
470 个评分
154 个审阅

课程概述

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 10.000 learners have enrolled so far!...

热门审阅

YK

Mar 02, 2017

Excellent course. The lecturer has written code snippets that let the students visualize the meaning and interrelationship of p-values confidence-intervals power effect-size bayesian-inference.

MR

Feb 22, 2018

Excellent course with a lot to learn. After 10 years in data analysis it provided me with great new insights and material to further improve my skills and understanding of data analysis

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76 - Improving your statistical inferences 的 100 个评论(共 153 个)

创建者 Sanjeev P

Nov 13, 2016

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

创建者 Anisha Z

Jan 07, 2018

Probably the most useful course I have ever taken. I think this is essential for anyone who does science. It provides a clear understanding of inferential statistics while discussing common pitfalls and myths surrounding p-values and confidence intervals. Assignments were very useful. Highly recommended!

创建者 Miroslav R

Feb 22, 2018

Excellent course with a lot to learn. After 10 years in data analysis it provided me with great new insights and material to further improve my skills and understanding of data analysis

创建者 Eva D P

Jan 23, 2017

Probably the best stats course I've ever taken (and also the most fun and enlightening)!

创建者 Jaroslav G

Feb 05, 2018

I found this course very well-structured and easily accessible and understandable even to students, while being highly profound and covering most important and and recent pressing topics in methodology and statistics.

创建者 侯静波

Jun 13, 2018

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.

创建者 Marcin K

Dec 22, 2016

Great course. Daniel explains everything clearly and with examples in R code which makes all of the concepts easier to understand. A must-take for experimental psychologists.

创建者 Martine K

Jun 21, 2018

Really great course! Was already familiar in statistics, but learned a lot about making inferences based on statistical tests. Lectures and assignments are very clear. Would recommend it to everyone interested in statistics.

创建者 Rizqy A Z

Jul 10, 2018

This course is immensely helpful to improve my area of expertise. This course also fills the gap of my previous formal training with current challenges in my career as a scientist

创建者 Danielle L

Aug 29, 2018

An excellent, informative, organized course. Highly recommended!

创建者 Benjamin F

Aug 16, 2018

Taking this course was the best decision of the start of my grad school. It has massively improved my ability to interpret other papers and plan my own experiments, as well as changing how I view psychology/science in general. Plus Daniel is a great teacher :)

创建者 Oaní d S d C

Aug 17, 2018

The course taught me a lot about data analysis and the philosophy of science. By focusing on the processes associated to doing science (data collection, theory generation, statistical inference) the course prepares you to design studies and think better about any area of research (it`s all data after all). But not just that, it made me rethink various things I do in life. I have to say that while, and now after, doing it I started to take a more scientific and data driven approach to all problems in my life. 10/10

创建者 Helén L

Aug 17, 2018

The course was great for refreshing my understanding of statistical inferences. Additionally, it provides an easy to understand introduction to bayesian thinking. The apps and websites, as well as the R-codes and excel-sheets provided alongside the assignments, and the lecture videos are of high quality and proof of a thorough and intesive preparation of the material. The material is very helpful, both for learners and for those teaching statistics to students. Plus, Professor Lakens lectures are entertaining and fun to watch.

I really enjoyed the course and have already recommended it to my department.

创建者 Bertin

Nov 17, 2018

This course is amazing, dynamic and entertaining. Daniel Lakens is brilliant.

创建者 Jose J P N

Oct 09, 2018

A great course to learn or refresh theoretical concepts behind statistical inferences. There is also a lot of hands-on material and additional content. I think I will come back to the videos and slides when I want to refresh some concepts.

创建者 Jan N

Oct 11, 2018

Nicely packed body of information necessary to understand your data and to infer any judgements about real world impact of scientific research. The course led me to question my way of creating inferences about my research and conclusions of others. Now, I can be more precise in formulating hypotheses and interpreting results in the way that is closer to truth. Thank you.

创建者 Ernesto M

Jul 30, 2018

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

创建者 Yoel S

Sep 16, 2018

One of the best online courses I've ever taken! (completed it just now). Great lectures, great materials, great assignments. Links and information for anyone wanting to go deeper on any topic. Brilliant and engaing lecturer who provides the information with so much passion and interest that it "catches on" to you. I especially liked how actual studies are used as examples for learning/assignments. Bottom line - in my opinion it's a must do course to anyone who is interested in inferential statistics.

创建者 Nareg K

Nov 30, 2018

Great course!

创建者 Kevin H

May 13, 2019

Very good introduction course. An improvement could be to include more high level summaries of each sections. I think it could help students better organize their thoughts.

创建者 Reuben A

Apr 17, 2019

The best statistics course I have ever taken

创建者 Andreas K

Jul 15, 2019

While the course is for researchers, also non-researchers like myself can get a better understanding for methods and pitfalls in science. You need to have prior knowledge of basic statistics and how to perform statistical tests, such as a t-test. I read up on the latter on the Internet, which proved sufficient.

Most examples are from psychology, but the principles are general. In this brief course, very little mathematics is used, but there are other sources for that. The section on r class effect sizes could have used some more work. (Or perhaps I should know more beforehand?) The final exam may ask questions not explicitly covered in the material; I do not recall any mention of Bonferroni correction, but this is perhaps so basic that it is considered a prerequisite.

创建者 Shambhavi

Jul 30, 2019

Excellent course, taught well with very useful assignments. Would recommend!

创建者 Thijs

Aug 14, 2019

Great course. Already had some knowledge about statistics, but this course really improved it.

创建者 Jose M S

Jun 17, 2017

Quite interesting and well structured. The contents of this course deserve a wide audience.