👉 Trend math, also known as time series analysis, focuses on identifying and forecasting patterns in data that change over time. The core idea is to model historical data points to predict future values, often by capturing underlying trends, seasonality, and cyclical patterns. A key trend in trend math is the linear trend, where data points generally increase or decrease steadily over time, often represented by a straight line in a graph. Non-linear trends, such as exponential or polynomial growth, also play a significant role, where changes accelerate or decelerate over time. Techniques like moving averages, regression analysis, and exponential smoothing are commonly used to extract these trends, helping analysts make informed predictions about future outcomes in fields like economics, finance, and environmental science.
