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.
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Improving Your Statistical Questions
Технический университет ЭйндховенаОб этом курсе
A basic knowledge of statistics and research methods is necessary. My previous MOOC 'Improving Your Statistical Inferences' is recommended.
Будет ли вашей компании выгодно обучить сотрудников востребованным навыкам?
Попробуйте Coursera для бизнесаЧему вы научитесь
Ask better questions in empirical research
Design more informative studies
Evaluate the scientific literature taking bias into account
Reflect on current norms, and how you can improve your research practices
Приобретаемые навыки
- Computational Reproducibility
- Meta-Analysis
- Experimental Design
- Statistical Inferences
- Philosophy of Science
A basic knowledge of statistics and research methods is necessary. My previous MOOC 'Improving Your Statistical Inferences' is recommended.
Будет ли вашей компании выгодно обучить сотрудников востребованным навыкам?
Попробуйте Coursera для бизнесаот партнера
Программа курса: что вы изучите
Module 1: Improving Your Statistical Questions
Module 2: Falsifying Predictions
Module 3: Designing Informative Studies
Module 4: Meta-Analysis and Bias Detection
Рецензии
- 5 stars89,21 %
- 4 stars7,84 %
- 3 stars2,94 %
Лучшие отзывы о курсе IMPROVING YOUR STATISTICAL QUESTIONS
Cracking - very informative, nice mixture of modes of learning, and engaging
Excellent! Would like only one addition, and that's a more extensive exercise on simulating data with general linear models
Daniel's second course as good as the first. He does a nice job!!
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Which previous knowledge is required?
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