Understanding Seasonality in Time-Series Analysis

Hard Time-series Analysis Seasonality

ABC Corp. has been analyzing its quarterly sales data over the last five years to identify patterns that can help in forecasting future sales. The data collected shows clear oscillations in sales figures corresponding to specific seasons of the year. For instance, sales typically peak during the holiday season in the fourth quarter and dip significantly in the first quarter post-holiday. The management suspects that this seasonal effect has a significant impact on their overall sales performance, and they wish to adjust their forecasts accordingly. They decide to employ a time-series decomposition method to quantify the seasonal effects on sales.

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

Seasonality refers to patterns in data that repeat at fixed intervals, typically correlated with seasonal changes in weather, holidays, or business cycles.

Seasonality is defined as the underlying long-term trend observed in time-series data, unrelated to seasonal factors, showing gradual shifts over time.

Seasonality only applies to monthly measurements and does not consider quarterly or yearly cyclical variations.

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