Product changes in manufacturing and storage are often time-dependent. Sometimes these changes are linear, sometimes cyclical and at other times chaotic. It is often not obvious that a time-dependent change is in fact occurring in some variable of interest. In this report we discuss methods for studying whether a trend exists and, if so, what the nature of that trend is. Data used to study this problem, observations collected sequentially over time, are referred to as a time series. Time series techniques can prove to be important in bringing to light underlying trends in data that may be evident through other techniques.
This technical report appears as:
Lampe, R. and Ennis, D. M. (2007). Discovering Time-Dependent Trends. IFPress, 10(1) 2-3.
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This technical report also appears in our book, Tools and Applications of Sensory and Consumer Science.