Comprehensive summary statistics
Measures of central tendency and variability
Tabulations and bar chart visualizations
Rudimentary distribution creation for discrete variables
Statistical fit tests for distributions
Utility dictionary for GOF tests
Decision tree classifier for categorical outcomes
K-nearest neighbors classification
K-nearest neighbors implementation variant
Binary classification using logistic models
Basic neural network models for prediction
Predictive modeling using OLS and other regressions
Ensemble classification using decision trees
Market basket and association rule mining
Mining insights from social media data
Unsupervised learning to group observations
Overview of mining methods and pipelines
Basic natural language processing and analysis
Handling missing values in datasets
Multiple imputation by chained equations
Tests for normal distribution assumptions
Dictionary for conducting normality tests
Identify and flag anomalous data points
Techniques to eliminate outliers
Mean, median, and model-based imputations
Apply transformations to normalize data
PCA and other techniques to reduce variables
Metrics for model accuracy and evaluation
Modularized descriptive statistics tools
Reusable code for frequency analysis
Encapsulated functions for GOF testing
Integrated stats toolkit
Module for normality testing
Ordinary Least Squares modeling tools
Tools for statistical transformations
Time series forecasting using classical methods
Moving averages and exponential smoothing
Seasonal-Trend decomposition using Loess
Modeling yes/no, on/off, and true/false decisions using binary optimization techniques
Formulating decisions over multiple stages under uncertainty using dynamic programming
Solving optimization problems where decision variables must take whole number values
Optimizing flows through networks such as supply chains, pipelines, and transportation routes
Building and solving general optimization models to support data-driven decision making
Evaluating how changes in parameters impact optimal solutions and decision robustness
Minimizing costs of shipping goods across origins and destinations using linear programming