1. for single exponential smoothing chosen alpha very close to zero means: select one

putting more weight to the earlier state, none of the above, putting equal weight to both recent and earlier events, putting more weight to the recent events

2. the best way to get the optimal value of alpha in single exceptional smoothing is by trial and error: true or false

3. One of the ways to see whether changing parameter alpha(from example 0.2 to 0.3) in SES(single exponential smoothing) has improve the accuracy of the models is: select one

to compare MAPE of one value with MAD of the other, to compare the same error metric(MAD, MSE, MAPE) for the two values of alpha, to compare MAPE of one value with MSE of the other, to compare MSE of one values with MAD of the other