Time Series with Trend

In a time series trend estimation can be used to express the long term increasing or decreasing tendencies that are statistically distinguishable from the random behavior of the system. A model can be used to describe such behavior of the observed data.

Linear time-series forecasting model is used when there is a trend in the underlying data which may be sufficiently represented by drawing a straight line and calculating its slope. Such a line must be drawn in a way that it “best fits” the data points of the scatter plot.

Many times a straight line is either misleading or insufficient; in such cases one may notice that parabola or a curve is a better fit instead of the straight line.

In some cases an exponential time series forecasting model is a better fit, specifically when the data series increases or decreases  at faster and faster rate as the values increase or decrease respectively.

In these set of slides we will take a look at estimating trends associated with time series data.

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