Time Series Prediction Project: Two choices
Option 1: Use one of the US Census time series linked https://www.census.gov/econ/currentdata/dbsearch?program=MRTS&startYear=1992&endYear=2017&categories=44X72&dataType=SM&geoLevel=US¬Adjusted=1&submit=GET+DATA&releaseScheduleId=%C2%A0 (Links to an external site.) (note that the Census will allow you to check “seasonally adjusted” or “not seasonally adjusted.” You’ll almost certainly want “not seasonally adjusted” since it will help you to show that you can deal with seasonality).
Option 2: Find another time series of interest to you on the internet (any time series OK, but be sure to include a link to the data. One option: choose any subcategory of the data from class!).
Whether you choose Option 1 or Option 2, perform a time series analysis. Consider is it horizontal? Does it show a trend? Seasonality? How about a non-seasonal cycle? Some textbooks including Business Analytics say that non-seasonal cycles must be longer than a year (and depending on your sampling frequency those might be the only cycles you can see in your data), but of course that’s not generally true. Biological rhythms are generally cyclic and less than a year in length, and it’s entirely possible to have cycles in the supply chain that repeat more often than yearly.
Consider smoothing (moving average or exponential smoothing). Include graphs of both. Do you believe they improve the model? Why or why not?
Here’s a quick and imperfect video (I forgot the camera was on! be merciful and toggle my face to the smaller screen!) showing you the basic steps, if it helps. I’m following Kylene Tyler’s “Project4Tutorials.docx” if you prefer that format. For more information on Time Series Analysis check out: https://en.wikipedia.org/wiki/Time_series
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