Logistic Forecasting

Listed below are topic(s) I would like for each of you to discuss throughout the week. Refer to the weekly materials, your textbook, and/or the GMC library when researching the topics for this Discussion Forum. Put your writing into your own words, do not copy directly from the source. If you incorporate scholarly/peer reviewed sources (http://gmcga.libguides.com/periodicals) in your posts be sure to cite (https://gmcga.libguides.com/citationmanagement/APA7th) them properly.

In your own words, discuss what forecast error represents.  Why is it important to measure?
In the time-series forecast methods, explain the advantages and disadvantages of simple moving averages, weighted moving averages, and exponential smoothing.  In your discussion, identify which situation(s) is best for one method and why.
For exponential smoothing , in what situation would you use a high alpha?  Or a low alpha?
In forecasting, why is it important to be able to detect trends? Or consider seasonal patterns?

Work Cited:
 Bruzda, J. (2020). Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches. Central European Journal of Operations Research, 28(1), 309336. https://doi.org/10.1007/s10100-018-0591-2