The MSE, mean squared error, is a measure of forecast accuracy and is the average of the squared forecast errors. Before this can be found, we first need to find the forecast values, forecast error, and squared forecast errors. Forecasts will be made using the most recent values known. There will be no forecast for the first month. The forecast value for month 2 will be the observed value from month 1, so the forecast value for month 2 is . The forecast value for month 3 will be the observed value from month 2, so the forecast value for month 3 is . This pattern will continue for the rest of the months. Complete the column for the forecast value in the table below. Month Value Forecast Value
1 22
2 30
3 26
4 31
5 27
6 26
7 31
Find the forecast for month 8 using this pattern.