Preparing an accurate forecast for an aggregated group of similar products is often easier than forecasting for an individual product separately.
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Q6: Cyclical factors are similar to seasonal factors,but
Q7: A moving average filters out the effects
Q8: Seasonal demand is measured in time periods
Q9: Random variation is caused by chance events
Q10: Seasonal patterns can be exhibited over a
Q12: Weighted moving average and exponential smoothing both
Q13: Fashion and economic conditions produce cycles.
Q14: Forecasting becomes more difficult the farther a
Q15: A time-series analysis considers cycles,trends,and seasonal variation
Q16: Sophisticated forecasting models using massive computing power
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