Answer (C) is correct . Time series analysis relies on past experience. Changes in the value of a variable may have several possible components including secular trends, cyclical variation, seasonality, and random variation. Seasonal variations are common in many businesses. A variety of methods exist for including seasonal variations in a forecasting model, but most methods use a seasonal index. Alternatively, seasonal variations can be removed from data by using a weighted average of several time periods instead of data from individual periods.
Answer (A) is incorrect because Adding a seasonality factor to, or subtracting it from, a forecast based on trend analysis is a means of adjusting for seasonality.
Answer (B) is incorrect because Seasonality factors cannot be ignored; they are reflected in the data and must be considered for a model to be accurate.
Answer (D) is incorrect because The seasonality adjustment for a single season’s data may be an increase or a decrease.
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