Work out time series seasonality strength instantly with clear inputs, formula shown and shareable results.
After STL decomposition into trend, seasonal and remainder components, strength is measured as 1 minus the remainder variance over the variance of the component plus remainder. Values near 1 mean the component explains almost all the variation that is not noise, and near 0 mean it explains almost none. This is a principled way to decide whether a seasonal model is warranted at all.
Component strength
Fs = 1 - Var(remainder) / Var(seasonal + remainder); Ft = 1 - Var(remainder) / Var(trend + remainder)
Yes, they are measured independently. Retail sales typically show high values for both, which is why models such as Holt-Winters carry separate trend and seasonal states.
Drop the seasonal terms. Fitting seasonality that is not there costs parameters and adds variance to the forecast without reducing bias.