Day131 - STAT Review: Classification (1)
Practical Statistics for Data Scientists: Naive Bayes (Theoretical Approach, Code Source, & Prediction)
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Day130 - STAT Review: Regression and Prediction (8)
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Day129 - STAT Review: Regression and Prediction (7)
Practical Statistics for Data Scientists: Stepwise Regression & Model Selection in Depth
Day128 - STAT Review: Revisiting Mathematics Theories (4)
Mathematical Principles: Non-parametric Inference (Wilcoxon Signed-Rank Test & Wilcoxon Rank-Sum Test)
Day127 - STAT Review: Revisiting Mathematics Theories (3)
Mathematical Principles: Inference on Proportions- Sample Size Estimation, Hypothesis Testing, and Chi-Squared Test
Day126 - STAT Review: Revisiting Mathematics Theories (2)
Mathematical Principles: Inference for Variance, Chi-Squared Distribution, F-Statistics, and Inference on Proportions (Wald & Wilson)
Day125 - STAT Review: Revisiting Mathematics Theories (1)
Mathematical Principles: Hypothesis Testing, Paired Samples, Independent Samples, and additional concepts.
Day124 - STAT Review: Regression and Prediction (6)
Practical Statistics for Data Scientists: Partial Residual Plots and Nonlinearity, Polynomial & Spline Regression, and Generalized Additive Models
Day123 - STAT Review: Regression and Prediction (5)
Practical Statistics for Data Scientists: Regression Diagnostics- Outliers, Influential Observations, and Heteroskedasticity
Day122 - STAT Review: Regression and Prediction (4)
Practical Statistics for Data Scientists: Interpreting the Regression Equation - Correlation, Multicollinearity, Confounding Variables, and Interactions