Understanding Seasonality in Time-Series Analysis

In the study of time-series data, seasonality refers to periodic fluctuations that occur at regular intervals over time, typically within a year. For example, retail sales often increase during the holiday season each year due to increased consumer spending.

Consider a time-series dataset representing quarterly sales figures for a company. These figures exhibit systematic patterns due to factors like seasonal demand, production cycles, or climatic variations. Understanding these patterns is crucial for forecasting and business decision-making.

Which of the following statements best describes seasonality in time-series data?