| abstract
| - Trend analysis (trend extrapolation) is a forecasting method based on identifying, based on historical data and observations, an ongoing change. The point of trend analysis is to identify the trend early, while it is still likely to continue in the future. Quantitative trend analysis deals mostly with data as opposed to information. Statistics pertaining to the subject are gathered and plotted along a time axis to produce a curve, which can be extrapolated into the future. An example of a quantitative trend is Moore's law, improved fuel efficiency of cars, the annual number of transplants and the number of cybernetically enhanced humans. Of course, the further in time the extrapolation, the greater the uncertainty of the event happening and there is no guarantee that the variable will continue to change the way it did in the past. This kind of trend analysis is normally used to draw attention to the forces that could change the extrapolated pattern. More sophisticated analysis (e.g. time series analysis) can be used to try to reveal different patterns. Trend analysis can also be used to identify qualitative trends, where the quantitative data cannot be obtained (example: globalisation). Characterising such trends requires creative and systemic thinking and is one of the most challenging aspects of futures research.
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