Smoother line

A line that is fitted to the data to explore the potential relationships between two variables, without fitting a specific model, such as a regression line or a theoretical distribution.  

One common technique for determining a smoothing line is called Lowess, which stands for LOcally-WEighted Scatterplot Smoother. The routine selects a fraction (default f = 0.5) of all points, using the data closest in x-value on either side of the (x,y) point. For each data point, Minitab performs a weighted linear regression, giving points closest to each x-value the greatest weight in the smoothing and limiting the influence of outliers. You can specify parameters to modify both the degree of smoothing and the influence of outliers.

You can add a smoother line to a scatterplot, matrix plot, histogram, or time series plot. Smoother lines are most useful when the curvature of the relationship does not change sharply.

In a time series plot, other techniques can be used to create smoother lines:

·    Moving Average - Averages consecutive observations

·    Single Exp Smoothing - Calculates dynamic estimates for a single component: the level.

·    Double Exp Smoothing - Calculates dynamic estimates for two components: level and trend.

·    Winter's method - Calculates dynamic estimates for three components: level, trend, and seasonal.

You can specify the weight of the smoothing parameter. The larger the weights, the more the smoothed values follow the data; the smaller the weights, the less jagged the pattern is in the smoothed values.