👉 Timing math, also known as time series analysis or temporal dynamics, involves using mathematical techniques to analyze and predict patterns in data that change over time. It focuses on understanding how variables evolve, interact, and influence each other across different time intervals. Key concepts include calculating rates of change (derivatives), identifying trends and cycles (using moving averages and Fourier transforms), and forecasting future values based on historical data. Techniques like exponential smoothing, ARIMA models, and machine learning algorithms are employed to model these temporal relationships, helping to make informed decisions in fields like finance, weather forecasting, and traffic management.
