What does a "moving average" help to eliminate in data analysis?

A moving average is a statistical technique used to smooth out fluctuations in data over a specified period, making trends easier to identify. It particularly excels in helping to eliminate seasonal variations, which are regular and predictable changes that occur at certain times of the year within data sets. By calculating the average of data points within a moving window, the noise created by seasonality is reduced, providing a clearer view of the underlying trend.

This approach is valuable in various fields, such as finance or sales forecasting, where seasonal peaks and troughs can obscure the overall performance. By focusing on moving averages, analysts can better identify long-term trends and patterns without the interference of these regular fluctuations.