20100320

Trend Analysis: see it 1st

Data Visualization can be a good thing for Trend Analysis: it allows to "see this" before "analyze this" and to take advantage of human eye ability to recognize trends quicker than any other methods. Dr. Ahlberg started (after selling Spotfire to TIBCO and claiming that "Second place is first loser") a "Recorded Future" to basically sell ... future trends in form (mostly) of Sparklines; he succeeded at least in selling RecordedFuture to investors from CIA and Google. Trend analysis is an attempt to "spot" a pattern, or trend, in data (in most cases well-ordered set of datapoints, e.g. by timestamps) or predict future events.

Visualizing Trends means in many cases either Time Series Chart (can you spot a pattern here with your naked eye?):



or Motion Chart (both best done by ... Google, see it here http://visibledata.blogspot.com/p/demos.html ) - can you predict the future here(?):



or Sparklines (I like Sparkline implementations by Qlikview and Excel 2010) - sparklines are scale-less visualization of "trends":



may be Scatter (Excel is good for it too):



and in some cases Stock Chart (Volume-Open-High-Low-Close, best done with Excel) - for example Microsoft stock is fluctuating near the same level for many years, so I guess there is no visible trend  here, which may be spells a trouble for Microsoft future (compare with visible trend of Apple and Google stocks):



Or you can see Motion, Timeline, Sparkline and Scatter charts alive/online below: for Motion Chart Demo, please Choose a few countries (e.g. check checkboxes for US and France) and then Click on "Right Arrow" button in the bottom left corner of the Motion Chart below:

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In statistics trend analysis often refers to techniques for extracting an underlying pattern of behavior in well-ordered dataset which would otherwise be partly hidden by "noise data". It means that if one cannot "spot" a pattern by visualizing such a dataset, then (and only then) it is time to apply regression analysis and other mathematical methods (unless you smart or lucky enough to remove a noise from your data). As I said in a beginning: try to see it first! However, extrapolating the past to the future can be a source for very dangerous mistakes (just check a history of almost any empire: Roman, Mongol, British, Ottoman, Austrian, Russian etc.)

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