- Level Professional
- Duration 18 hours
- Course by Eindhoven University of Technology
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Offered by
About
This course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions. In practical hands on assignments you will learn techniques and tools that can be immediately implemented in your own research, such as thinking about the smallest effect size you are interested in, justifying your sample size, evaluate findings in the literature while keeping publication bias into account, performing a meta-analysis, and making your analyses computationally reproducible. If you have the time, it is recommended that you complete my course 'Improving Your Statistical Inferences' before enrolling in this course, although this course is completely self-contained.Modules
Course Introduction (Read before Starting)
2
Assignment
- Consent Form for Use of Data
- Welcome: Short Survey
1
Readings
- Download Course Materials and Course Structure (Must Read)
Lecture 1.1: Improving Your Statistical Questions
1
Videos
- Lecture 1.1: Improving Your Statistical Questions
Lecture 1.2: Do You Really Want to Test a Hypothesis?
1
Videos
- Lecture 1.2: Do You Really Want to Test a Hypothesis?
Lecture 1.3: Risky Predictions
1
Videos
- Lecture 1.3: Risky Predictions
Assignment 1.1: Testing Range Predictions
1
Assignment
- Answer Form Assignment 1.1: Testing Range Predictions
1
Readings
- Assignment 1.1: Testing Range Predictions
Lecture 2.1: Falsifying predictions in theory
1
Videos
- Lecture 2.1: Falsifying Predictions in Theory
Lecture 2.2: Setting the Smallest Effect Size Of Interest
1
Videos
- Lecture 2.2: Setting the Smallest Effect Size Of Interest
Assignment 2.1: The Small Telescopes Approach to Setting a SESOI
1
Assignment
- Answer Form Assignment 2.1: The Small Telescopes Approach to Setting a SESOI
1
Readings
- Assignment 2.1: The Small Telescopes Approach to Setting a SESOI
Assignment 2.2: Setting the SESOI Based on Resources
1
Assignment
- Answer Form Assignment 2.2: Setting the SESOI Based on Resources
1
Readings
- Assignment 2.2: Setting the SESOI Based on Resources
Lecture 2.3: Falsifying Predictions in Practice
1
Videos
- Lecture 2.3: Falsifying Predictions in Practice
Assignment 2.3: Equivalence Testing
1
Assignment
- Answer Form Assignment 2.3: Equivalence Testing
1
Readings
- Assignment 2.3: Equivalence Testing
Lecture 3.1: Justifying Error Rates
1
Videos
- Lecture 3.1: Justifying Error Rates
Assignment 3.1: Confidence Intervals for Standard Deviations
1
Assignment
- Answer Form Assignment 3.1: Confidence Intervals for Standard Deviations
1
Readings
- Assignment 3.1: Confidence Intervals for Standard Deviations
Lecture 3.2: Power Analysis
1
Videos
- Lecture 3.2: Power Analysis
Assignment 3.2: Power Analysis for ANOVA Designs
1
Assignment
- Answer Form Assignment 3.2: Power Analysis for ANOVA Designs
1
Readings
- Assignment 3.2: Power Analysis for ANOVA Designs
Lecture 3.3: Simulation
1
Videos
- Lecture 3.3: Simulation
Lecture 4.1: Mixed Results
1
Videos
- Lecture 4.1: Mixed Results
Assignment 4.1: Likelihood of Significant Findings
1
Assignment
- Answer Form Assignment 4.1: Likelihood of Significant Findings
1
Readings
- Assignment 4.1: Likelihood of Significant Findings
Lecture 4.2: Intro to Meta-Analysis
1
Videos
- Lecture 4.2: Intro to Meta-Analysis
Assignment 4.2: Introduction to Meta-Analysis
1
Assignment
- Answer Form Assignment 4.2: Introduction to Meta-Analysis
1
Readings
- Assignment 4.2: Introduction to Meta-Analysis
Lecture 4.3: Bias Detection
1
Videos
- Lecture 4.3: Bias Detection
Assignment 4.3: Detecting Publication Bias
1
Assignment
- Answer Form Assignment 4.3: Detecting Publication Bias
1
Readings
- Assignment 4.3: Detecting Publication Bias
Assignment 4.4: Checking Your Stats
1
Readings
- Assignment 4.4: Checking Your Stats
Lecture 5.1: Computational Reproducibility
1
Videos
- Lecture 5.1: Computational Reproducibility
Assignment 5.1: Computational Reproducibility
1
Readings
- Assignment 5.1: Computational Reproducibility
Lecture 5.2: Philosophy of Science in Practice
1
Videos
- Lecture 5.2: Philosophy of Science in Practice
Assignment 5.2: Does Your Philosophy of Science Matter in Practice?
1
Readings
- Assignment 5.2: Does Your Philosophy of Science Matter in Practice?
Lecture 5.3: Scientific Integrity in Practice
1
Videos
- Lecture 5.3: Scientific Integrity in Practice
Assignment 5.3: Applied Research Ethics
Final Exam
1
Assignment
- Graded Final Exam
Auto Summary
Enhance your empirical research with "Improving Your Statistical Questions," a professional-level course by Coursera. Dive into designing informative studies, questioning norms, and refining research practices. Gain hands-on experience with techniques like effect size consideration, sample size justification, literature evaluation, meta-analysis, and computational reproducibility. Recommended for those who have completed "Improving Your Statistical Inferences," this 1080-minute course offers Starter and Professional subscription options, ideal for researchers looking to elevate their statistical questioning skills.

Daniel Lakens