Forecasting techniques that should be considered when forecasting a seasonal series.

1. List some of the forecasting techniques that should be considered when forecasting a seasonal series. Give examples of situations in which these techniques would be applicable

2. List some of the forecasting techniques that should be considered when forecasting a cyclical series. Give examples of situations in which these techniques would be applicable.

Descriptions are provided for several types of series: random, stationary, trending, and seasonal. Identify the type of series that each describes.

a. The series has basic statistical properties, such as the mean and variance, that remain constant over time.

b. The successive values of a time series are not related to each other.

c. A high relationship exists between each successive value of a series.

d. A significant autocorrelation coefficient appears at time lag 4 for quarterly data.

e. The series contains no growth or decline.

f. The autocorrelation coefficients are typically significantly different from zero for the first several time lags and then gradually decrease toward zero as the number of lags increases

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