Time-Series Analysis is a statistical technique used to analyze data points collected or recorded at specific time intervals. It helps identify trends, seasonal patterns, and cyclical behaviors in the data, making it useful for forecasting future values. Common applications include economic indicators, stock prices, and weather data. This analysis involves various methods, such as moving averages and exponential smoothing, to smooth out fluctuations and highlight underlying patterns. By understanding these patterns, businesses and researchers can make informed decisions based on historical data, improving their ability to predict future outcomes.