Chevron Left
Back to Improving your statistical inferences

Learner Reviews & Feedback for Improving your statistical inferences by Eindhoven University of Technology

4.9
443 ratings
146 reviews

About the Course

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!...

Top reviews

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

Filter by:

26 - 50 of 145 Reviews for Improving your statistical inferences

By Sebastian U

Mar 26, 2018

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

By Caroline W

Jun 17, 2017

I thought this was an excellent and enjoyable course. Daniel Simons is a great teacher, and I learned a lot as well as picking up some practical tools for the future, such as easy to use spreadsheets to calculate and convert effect sizes, and confidence intervals. I'm an R novice, but got on fine with it and really appreciated the pedagogical value of the R-simulations.

By Benedikt L

Jun 22, 2018

This course was a great opportunity to reflect my statistical inference knowledge. I hold a master of science in psychology and already learned most of the stuff presented. But the course gave a great overview of the fundamentals of statistical inferences and made me really think twice about how to conduct science properly. I was able to deepen my knowledge and improved my understanding of the statistical fundamentals. I even learned a lot new things that were not covered in the university courses I had! The course is thus not only for beginners, but also for people who already have some knowledge in statistics. Also the course was really enjoyable and had just the right amount of information within each section. All the materials - videos, examples, further readings, exercises and pop-up-quizes varied and were very well designed! The examples were practically relevant (often based on real studies in the literature and not just artificially constructed) and sometimes also really humorous. Thanks a lot to the lecturer for this great opportunity to improve my knowledge!

By Alexander P

Jul 23, 2017

Phenomenal course!

By Jayadev H

May 11, 2018

Sooo good! Cant even begin to explain how essential and wonderful this understanding is!

Great thanks to Dr Daniel! Such an expert in the field!

Thank you Dr!

By Gerald R

Sep 02, 2017

a very thoughtful introduction to the different approaches of statistical reasoning

By 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!

By 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.

By 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.

By martin j k

Nov 06, 2017

E

x

c

e

l

l

e

n

t

c

o

u

r

s

e

!

By Stefan W

Dec 28, 2016

This course is totally awesome! Statistical inference is critical in any science. Why collect data if we do not know what to infer from the data? Unfortunately, many disciplines use outdated or incorrect practices. This course provides an excellent review of state of the art approaches and provides students with many thought-proving opportunities to practice their inferential skills. As a professor of Psychology, I am not embarrassed to say that I learned lots from this course. The lectures, demos, and R scripts are useful tools that I will integrate in my teaching and my own research. Although the course topic is challenging, the course is organized well and does not drown students in technical terms. However, if you take this course, you better be serious and dedicated. The course is challenging, but the knowledge and skills gained are a rewarding experience.

By 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.

By 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!

By Justyna J Z

Apr 29, 2018

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

By Biju S

Dec 05, 2017

Very interesting course

By Davide F S

May 21, 2017

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

By Brendan P

Oct 21, 2017

Excellent content and delivery throughout.

By Xiwen O

Dec 26, 2017

Very great work to help people to listen this great courses!

By Michael E

Jun 25, 2017

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

By Jesús D Z M

Jun 12, 2017

very, very great course about inferential statistics

By Muhammad T S

Nov 09, 2017

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

By Farid

Mar 12, 2017

Exactly what i needed. But now it

By Sandra V

Dec 10, 2016

Extremely useful cours, especially the first 5 weeks! Pleasant and enjoyable. Definitely recommended!

By Rikki L

Apr 30, 2018

The course is excellent. I only wish that I'd enrolled sooner!

By Syarif M

Dec 03, 2016

highly recomended for all level. The explanation is very beginners friendly.