返回到 Improving your statistical inferences

4.9

462 个评分

•

150 个审阅

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!...

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.

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

筛选依据：

创建者 Hollin V

•Sep 20, 2017

Concepts are explained in an easy-to-understand way with a good use of analogies. Homework assignments are straightforward and useful. I like the way he teaches using simulations. He encourages students to play around with his simulations to discover how changes in the simulations' inputs affect the results.

创建者 Gerald R

•Sep 02, 2017

a very thoughtful introduction to the different approaches of statistical reasoning

创建者 Oleksandr H

•Nov 26, 2016

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!

创建者 Yaron K

•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.

创建者 Md. M I C

•Jan 03, 2017

It is good indeed. Such course is needed more on Coursera.

创建者 Jonas S

•Nov 16, 2016

Very well designed course, from a didactic as well as from an entertainment point of view. I was able to close many gaps in my inferential statistics knowledge and now feel much more confident in my interpretations.

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 Wilte Z

•Oct 23, 2016

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

创建者 Matti H

•Dec 13, 2016

I encourage all my friends in research to not do anything before doing this course! The pedagogical touch is different to any stats classes I've been on or stats MOOCs I've taken. After many lectures, I was just left staring at the screen, with the phrase "I must tell everyone" repeating in my head :)

创建者 Tiago C Z

•Jun 19, 2018

This course changed my concepts not only about statistics but about research and science. Daniel Lakens is a fantastic lecturer and scientist. I can't recommend this course enough.

创建者 Vít G

•Nov 12, 2016

Dear Daniel,Let me thank you for this marvel of yours. Your course helped me to revise and to (re)structure previously learned issues, it enriched me with new contexts that were presented in a truly enjoyable way, and last but not least, it gave me completely new insights including the role of simulations in teaching.Many thanks for your work!

创建者 Ramiro B

•Nov 06, 2017

I really like this class, it was very useful and the content was high quality. My only issue - which might have nothing to do with the class or the instructor - was that the exams were really long and boring. It would have been more enjoyable to be to have shorter, more focused examinations instead of a long exam at the end of a section or at the end of the class. EdX does this better.

创建者 Justyna J Z

•Apr 29, 2018

Very engaging, I love the way this course is taught!

创建者 Biju S

•Dec 05, 2017

Very interesting course

创建者 marcus n

•Feb 04, 2017

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

创建者 Pavol K

•Aug 16, 2017

Amazing course. Definitely worth to accomplish. Highly recommended for every researcher, lecturer, PhD. student or student that is interested in prestent state of art regarding choosen important topics statistics and methodology, especially in Psychology.

创建者 Davide F S

•May 21, 2017

Clear, concise, and engaging explanation of many statistical concepts that can be readily applied in research.

创建者 Brendan P

•Oct 21, 2017

Excellent content and delivery throughout.

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 Reuben A

•Apr 17, 2019

The best statistics course I have ever taken

创建者 Rodney K

•May 10, 2019

Very comprehensive and enjoyable course, highly recommended.

创建者 Nicholas

•Apr 28, 2019

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

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.