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A personal blog about data visualization and data analysis.
Welcome to my blog!
Here I will share some ideas about dataviz and data science.
- Data collection;/statistics/data_collection;1
- Things that could go wrong;/statistics/problem_solving_issues;2
- The problem solving workflow;/statistics/problem_solving;3
- Mixed effects models with more than two levels;/statistics/three_levels;4
- Leveraging mixed-effect models;/statistics/bambi_multilevel;5
- Random models and mixed models;/statistics/random_models;6
- Hierarchical models and meta-analysis;/statistics/hierarchical_metaanalysis;7
- Hierarchical models;/statistics/hierarchical_models;8
- Poisson regression;/statistics/poisson_regression;9
- Logistic regression;/statistics/logistic_regression;10
- Robust linear regression;/statistics/robust_regression;11
- Multi-linear regression;/statistics/multivariate_regression;12
- Linear regression with binary input;/statistics/regression_binary_input;13
- Introduction to the linear regression;/statistics/regression;14
- Model comparison, cont.;/statistics/model_averaging_cont;15
- Model comparison;/statistics/model_averaging;16
- Re-parametrizing your model;/statistics/reparametrization;17
- Predictive checks;/statistics/predictive_checks;18
- Trace inspection;/statistics/trace_inspection;19
- Introduction to the Bayesian workflow;/statistics/bayesian_workflow;20
- Mixture models;/statistics/mixture;21
- Multidimensional distributions;/statistics/categories;22
- The Gaussian model;/statistics/reals;23
- Bonus: counting animals in a park;/statistics/hypergeom;24
- The Negative Binomial model;/statistics/negbin;25
- The Poisson model;/statistics/poisson;26
- The Beta-Binomial model;/statistics/betabin;27
- Section introduction;/statistics/simple_models_intro;28
- Some notation about probability;/statistics/probability_reminder;29
- How does MCMC works;/statistics/mcmc_intro;30
- Introduction to Bayesian inference;/statistics/bayes_intro;31
- An overview to statistics;/statistics/preface;32
- The Gestalt principles;/dataviz/gestalt;33
- Design tricks;/dataviz/design-introduction;34
- How to choose a color map;/dataviz/palettes-introduction;35
- Introduction to color perception;/dataviz/color-introduction;36
- Drawing is redrawing;/dataviz/gender-economist;37
- Visual queries;/dataviz/visual-queries;38
- Channel effectiveness;/dataviz/effectiveness;39
- Evolutions of the line chart;/dataviz/linechart-evolution;40
- Beyond the 1D scatterplot;/dataviz/scatterplot-evolution;41
- Perception;/dataviz/perception;42
- Fundamental charts;/dataviz/fundamental-charts;43
- Marks and channels;/dataviz/marks-channels;44
- Data abstraction;/dataviz/data-types;45
- Data visualization;/dataviz/dataviz;46
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