We investigated the required transformations for variance stabilization and decided to take logarithms in the case of Boots, Booties and Flats data (for more details see Cryer and Chan shows ACF and PACF for the five retail series after transforming. It can be seen that in general the sample ACFs decay very slowly at regular lags and at multiples of seasonal period 12 PACFs have a large spike at lag 1 and cut off to zero after lag 2 or 3, suggesting that seasonal and/or ordinary differencing might be necessary.