The moving averages method refers to a forecasting method...

The moving averages method refers to a forecasting method that a. is used when considerable trend, cyclical, or seasonal effects are present. b. uses the average of the most recent data values in the time series as the forecast for the next period. c. uses regression relationship based on past time series values to predict the future time series values. d. relates a time series to other variables that are believed to explain or cause its behavior.

A forecasting technique referred to as moving averages uses the average or mean of the most recent $n$ periods to forecast the next value for time series data. With a three-period moving average, the most recent three periods of data are used in the forecast computation. Consider a product with the following demand for the first three months of the current year: January (800 units), February (750 units), and March (900 units). a. What is the three-month moving average forecast for April? b. A variation of this forecasting technique is called weighted moving averages. The weighting allows the more recent time series data to receive more weight or more importance in the computation of the forecast. For example, a weighted three-month moving average might give a weight of 3 to data one month old, a weight of 2 to data two months old, and a weight of 1 to data three months old. Use the data given to provide a three-month weighted moving average forecast for April.

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