Time series methods take into account possible
internal structure in the data
Time series data often arise when monitoring industrial processes or
tracking corporate business metrics. The essential difference between
modeling data via time series methods or using the process monitoring
methods discussed earlier in this chapter is the following:
Time series analysis accounts for the fact that data points taken
over time may have an internal structure (such as autocorrelation, trend
or seasonal variation) that should be accounted for.
This section will give a brief overview of some of the more widely
used techniques in the rich and rapidly growing field of time series
modeling and analysis.