Answers

Here are the answers to the preceding questions:

1. The number is up to the researcher – for example, we can use a bimonthly, quarterly, or semester time period when calculating the moving average.
2. No. Autocorrelation is a key factor in calculating future values because our forecast depends on past data to make predictions.
3. The cyclical seasonal component shows the increasing and decreasing values of the forecast based on the past data.
4. Multiply the season component by the trend of linear regression.
5. It shows the distance between the data and the CMA line.