Time Series Analysis

Time Series Analysis is a statistical and analytical technique used to examine data points collected or recorded at specific time intervals. It focuses on understanding underlying patterns such as trends, seasonality, and cyclical behavior over time. This type of analysis is essential for forecasting future values, detecting anomalies, and identifying correlations in temporal data. Common methods include ARIMA, exponential smoothing, and machine learning models tailored for sequential data. Time series analysis is widely used in fields such as finance, economics, supply chain, healthcare, and weather prediction to support data-driven decision-making and planning.