Trend Analysisoverview how to example data see also
Trend AnalysisStat > Time Series > Trend Analysis
Trend analysis fits a general trend model to time series data and provides forecasts. Choose among the linear, quadratic, exponential growth or decay, and S-curve models. Use this procedure to fit trend when there is no seasonal component to your series.
Variable: Enter the column containing the time series.
Model Type: Select the model that you want. Use care when interpreting the coefficients from the different models, as they have different meanings. See [4] for details.
Linear: Choose to model linearity in the trend. The linear trend model is the default model used in trend analysis.
Quadratic: Choose to model curvature in the trend.
Exponential growth: Choose to model exponential growth or decay.
S-Curve (Pearl-Reed logistic): Choose to model an S-shaped curve. You cannot have missing data when fitting the S-curve model.
Generate forecasts: Check to generate forecasts.
Number of forecasts: Enter an integer to indicate how many forecasts that you want.
Starting from origin: Enter a positive integer to specify a starting point for the forecasts. For example, if you specify 4 forecasts and 48 for the origin, Minitab computes forecasts for periods 49, 50, 51, and 52. If you leave this space blank, Minitab generates forecasts from the end of the data. Minitab uses data up to the origin for fitting the trend model used to generate forecasts.