[updated] | Seasonal Index

After dividing actual by the seasonal index, you get , which reveals the true trend and cycle.

[ \textSeasonal Ratio = \frac\textActual Value\textCentered Moving Average ]

(We’ll skip full arithmetic for brevity – but you’d smooth the data.) seasonal index

This ratio represents the combined effect of seasonality and random noise. Group all ratios by month (or quarter, etc.) and calculate the median or mean (median is less sensitive to outliers). Step 4: Adjust So That Average = 1 If the average of your raw seasonal indices is not exactly 1, adjust them:

[ \textAdjusted Index_i = \frac\textRaw Index_i\textMean of Raw Indices ] After dividing actual by the seasonal index, you

| Year | Q1 | Q2 | Q3 | Q4 | |------|----|----|----|----| | 2022 | 80 | 120 | 100 | 140 | | 2023 | 90 | 130 | 110 | 150 |

Now each index shows the seasonal effect relative to the overall average. Suppose quarterly sales (in $1,000) for two years: Step 4: Adjust So That Average = 1

[ \textActual = \textTrend \times \textSeasonal \times \textIrregular ]