The following monthly sales of chocolate boxes (in thousands of AUS dollars) have been recorded for January, February, March, and April, respectively: 9.5, 8, 9, 9. Examining the forecasting accuracy for the month of April only:  Explain which of the following forecasting method would you recommend: (i) the Naïve method, (ii) the Average method, or (iii) the Simple exponential smoothing method (assuming alpha= 0.8 and initial state (in December) of 8.5)

Naive Method:

Using the prior observation as the forecast without making any changes is known as a naïve forecast. Due to the persistence of the previous observation, it is frequently referred to as the persistence forecast.

Moving average forecast method:

Long-term trends can be predicted statistically using the moving average forecast method. The method illustrates shifting the range while taking the average of a group of numbers in that range.

Simple exponential method:

The time series forecasting method single exponential smoothing is used for univariate data without a trend or seasonality. It is also known as Simple Exponential Smoothing. The sole necessary parameter is the smoothing coefficient or factor, commonly abbreviated as alpha. This variable regulates the exponential decay rate to which the influence of the observations made at earlier time steps is subjected. A value between 0 and 1 is typically used for alpha. Smaller numbers indicate that more of the history is used for making predictions, whereas larger values indicate that the model focuses mostly on the most recent historical observations.