Insights, tutorials, and thoughts on neuroscience, computational methods, and research methodologies.
Learn how to create files for 3D printing complex models!
A comprehensive guide to using Analysis of Covariance (ANCOVA) in R.
A brief guide to using ANOVA in R for statistical analysis.
Understanding how broken stick models can be applied in Principal Component Analysis.
Thoughts on evidence-based approaches to drug policy and regulation.
Analyzing consumer behavior patterns through data science techniques.
Common mistakes in cross-validation and how to avoid them.
Introduction to frequentist statistical methods and concepts.
Advanced concepts in frequentist statistical analysis.
Complex applications of frequentist statistical methods.
How Independent Component Analysis helps separate signals from noise in complex datasets.
Understanding and modeling statistical interactions in data analysis.
Using L1 regularization for feature selection and sparsity in machine learning models.
Understanding L2 regularization and ridge regression techniques.
Applying linear regression techniques to analyze relationships in datasets.
Advanced multivariate analysis techniques using MANCOVA.
Understanding multivariate analysis of variance for complex datasets.
Essential metrics for evaluating machine learning classification models.
Understanding Principal Component Analysis for dimensionality reduction.
Thoughts on the current state of academic publishing and access to research.
Reflections on beginning the PhD journey and what to expect.
Reflections on the PhD application process and lessons learned.
A comprehensive guide to understanding and applying t-tests.
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