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Contains inferential statistical practices for machine learning models and analyses. Using Python and developing statistical thinking to work with a limited sample of data and be able to generate predictions about it. Applying confidence intervals to estimate unknown values. Using bootstrapping to simulate data acquisition repeatedly. Development of hypotheses of their models. Sampling of populations to facilitate analysis.
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Upload readme.md with item list for files list
10fb209View on GitHubMerge branch 'main' of https://github.com/ndcastillo/inferential-statistics-DS-AI
cd012f6View on GitHubAdd new articles as t-student, Pearson Coefficient, ANOVA, Bootstraping and their application in Python
00e70a8View on GitHubAdd '15 Tipos de errores.md' file that contain error's theory
49e373cView on GitHubRename file '13 Pruebas de hipotesis.md' to '14 Pruebas de hipotesis.md'
2f71d38View on GitHub