In statistics, a data point is a single typedmeasurement. Here type is used in a way compatible with datatype in computing; so that the type of measurement can specify whether the measurement results in a Boolean value from {yes, no}, an integer or real number, or some vector or array. The implication of point is therefore that the data may be plotted in a graphic display, but in many cases the data are processed numerically before that is done.
The datapoint to be smoothed has the largest weight and the most influence on the fit.
Datapoints outside the span have zero weight and no influence on the fit.
For example, when you smooth the datapoint with the smallest predictor value, the shape of the weight function is truncated by one half, the leftmost datapoint in the span has the largest weight, and all the neighboring points are to the right of the smoothed value.
Some data is recorded based on a small area around the point, the field where the datapoint is located, or along a transect going through the datapoint.
A point that had a landuse value of corn or soybeans and a earth cover value of over 90% row crop was separated into a group eligible for classification of the image (pure group).
A point that had a landuse of grass pastureland or hayland and a earth cover of over 90% grass herbaceous as added to the pure group as was a point that had a landuse of forest and earth cover of over 90% tree or shrub.
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