How do we measure a seasonal effect and remove it to compare periods fairly?
Calculate seasonal indices, deseasonalise and reseasonalise a time series, and interpret seasonal indices in context.
How to calculate seasonal indices that sum to the number of seasons, deseasonalise data by dividing by the index, reseasonalise by multiplying, and interpret what each index means.
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What this dot point is asking
You must calculate seasonal indices, use them to deseasonalise and reseasonalise, and explain what an index value means in words.
What a seasonal index is
A seasonal index for a season is the ratio of that season's typical value to the overall seasonal average. An index of means the season runs above average; means below.
Deseasonalising and reseasonalising
Removing the seasonal effect lets you compare periods and see the underlying trend.
Deseasonalised figures are what the value "would have been" without the seasonal swing. Reseasonalising is the reverse, used to turn a trend-line forecast back into an actual seasonal prediction.
Calculating indices from raw data
When you are given raw seasonal data rather than the averages, first find the average value for each season across all the years recorded, then divide each seasonal average by the overall average of those seasonal averages. If the resulting indices do not sum exactly to the number of seasons because of rounding, multiply each one by a small correction factor so they do. This correction keeps the indices internally consistent and is expected in a full solution.
Interpreting indices in context
A complete interpretation names the season, the percentage above or below average, and the practical meaning, for example that Q4 is the quietest quarter because its index is the lowest. Examiners reward this plain-language reading as much as the arithmetic. A business might use a high summer index to justify extra staff, or a low winter index to plan maintenance, so the index is not just a number but a planning tool.