<Li> Prediction intervals, similar to confidence intervals </Li> <Li> Reference class forecasting </Li> <P> Seasonality is a characteristic of a time series in which the data experiences regular and predictable changes which recur every calendar year . Any predictable change or pattern in a time series that recurs or repeats over a one - year period can be said to be seasonal . It is common in many situations--such as grocery store or even in a Medical Examiner's office--that the demand depends on the day of the week . In such situations, the forecasting procedure calculates the seasonal index of the "season"--seven seasons, one for each day--which is the ratio of the average demand of that season (which is calculated by Moving Average or Exponential Smoothing using historical data corresponding only to that season) to the average demand across all seasons . An index higher than 1 indicates that demand is higher than average; an index less than 1 indicates that the demand is less than the average . </P> <P> The cyclic behaviour of data takes place when there are regular fluctuations in the data which usually last for an interval of at least two years, and when the length of the current cycle cannot be predetermined . Cyclic behavior is not to be confused with seasonal behavior . Seasonal fluctuations follow a consistent pattern each year so the period is always known . As an example, during the Christmas period, inventories of stores tend to increase in order to prepare for Christmas shoppers . As an example of cyclic behaviour, the population of a particular natural ecosystem will exhibit cyclic behaviour when the population increases as its natural food source decreases, and once the population is low, the food source will recover and the population will start to increase again . Cyclic data cannot be accounted for using ordinary seasonal adjustment since it is not of fixed period . </P>

Which method of forecasting uses averages to predict future weather
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