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Introductory presentation on the normal distribution with practical examples, plots, and theoretical foundations applied to Statistics.
Visual and theoretical foundations: histograms, Q–Q plots, Law of Large Numbers, and Central Limit Theorem as the basis for approximate normality.
Practical foundations for standardization (z-score), probability lookup in the z-table, and comparative applications.
Introdução prática à padronização (escore‑z), leitura da tabela‑z e aplicações: comparação de desempenhos, interpretação de probabilidades, percentis e normal inversa.
This course aims to present, in an accessible and applied way, the fundamentals of the normal distribution, also known as the Gaussian distribution, supported by graphical visualizations and computational tools.
Complete Statistics courses with theory, practical applications, visualizations, and solved exercises in R and Excel.
Recommended reading path for the Statistics Section of Blog do Marcellini. Includes suggested order for courses and articles, based on complexity level and application.
Explore essential statistical concepts with a focus on applications, data interpretation, visualizations, and theoretical foundations. Includes full courses, solved examples, and reading guides.
