Fundamental statistical concepts, including data collection, sampling, and summary measures, alongside a foundation in inference through estimation and hypothesis testing. It integrates Exploratory Data Analysis (EDA) for modern data perspectives and provides hands-on training with appropriate statistical software.

Essential skills required to use R and RStudio for basic programming tasks. Participants will learn to use the Tidyverse ecosystem for importing and exporting data, performing data wrangling, and creating impactful visualizations to generate replicable outputs.

Explore methodologies for forecasting time series data through classical smoothing procedures and the implementation of ARIMA models. Participants will learn to analyze time series components, address data gaps, and perform stationarity tests to generate reliable, data-driven forecasts.