Data Science Tasks
Intro
Statistical Methods
Fitting Distributions
Continuous Distributions
Discrete Distributions
Hypothesis Testing
Parameter Estimation
Sample Size and Power
Proportions
T-test
Chi-square
ANOVA
Survival Analysis
Experimental Design
Completely Random Design
Random Complete Block Design
Contingency Tables
Principal Components
Eigen Values and Statistical Distance
Regression Methods
Matrix Regression
Logistic Regression
Multinomial Logistic Regression
Poisson Regression
Clustering Methods
Kmeans Clustering
Hierarchical Clustering
Forecasting
Basic Graphical Methods for Time Series
Generate Time Series Data
0.0.1
Manually Generated Series
Auto Generated Series
ARIMA Modeling
VAR Modeling
Machine Learning
Neural Network
Random Forest
Gradient Boosting
Support Vector Machines
Overfitting
Simulation
Bootstrap Simulation
Visualization
Building Maps with choropleth and ggplot
Data Science Tasks
Regression Methods