季节性调整计算器
对时间序列数据进行季节性调整，消除季节波动。
Seasonally Adjusted Value
120.0000
Seasonally Adjusted Value vs Observed Value
公式
How to Seasonally Adjust Data
Formula
Adjusted Value = Observed Value / Seasonal Index
Seasonal adjustment removes predictable seasonal patterns from data, revealing the underlying trend. A seasonal index above 1 means the season inflates the value; below 1 means it deflates it. Dividing by the index normalizes the value as if there were no seasonal effect.
计算示例
December sales are $150 with a seasonal index of 1.25 (holiday boost).
- 01Adjusted = 150 / 1.25 = 120
- 02Seasonal effect = 150 - 120 = 30
- 03The seasonal boost accounts for $30 (25%) of the observed value
- 04The underlying (de-seasonalized) value is $120
常见问题
How are seasonal indices calculated?
Typically by computing the ratio of each period's value to the moving average centered on that period, then averaging these ratios across multiple years. The indices should average to 1.0 across all seasons.
Why is seasonal adjustment important?
It allows meaningful comparison across periods. Without adjustment, December retail sales always look great and January looks bad, obscuring the real trend. Government statistics (GDP, unemployment) are usually reported seasonally adjusted.
Is multiplicative the only seasonal model?
No. Additive seasonal adjustment subtracts the seasonal component instead of dividing. Multiplicative models are used when seasonal variation grows with the level of the series; additive when it is constant.
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