Course 8 Time Series Analysis

Time Series Analysis is a powerful statistical technique used to analyze and interpret data collected over time. It focuses on identifying patterns, trends, and underlying structures within data that evolve sequentially. By examining historical data, time series analysis allows forecasting future values, understanding cyclical behavior, detecting anomalies, and making informed decisions across various fields, such as economics, finance, and environmental science. Key concepts in time series analysis include trend, seasonality, autocorrelation, stationary, and forecasting models like ARIMA (Auto Regressive Integrated Moving Average) and Exponential Smoothing. This chapter will explore the theoretical foundations and practical applications of time series analysis, emphasizing the tools and techniques used to model and predict temporal data.