Linear regression by least squares – Rockwell Automation FactoryTalk Historian SE ProcessBook 3.2 User Guide User Manual

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FactoryTalk Historian ProcessBook User Guide

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<index>, <time>, <value>, <status>
<index>, <time>, <value>, <status>

Tag, <tag name>
Start Time, <start time>
End Time, <end time>
Count, < number of points paired>
Mean, <mean>
STDEV, <standard deviation>
Correlation, <correlation coefficient>
Slope, <slope>
Intercept, <intercept>
Data Type, <data type>
Index, Time, Value, Status
<index>, <time>, <value>, <status>
<index>, <time>, <value>, <status>

Etc.

Linear Regression by Least Squares

The best-fit linear regression line is a straight line that attempts to
summarize the trend of the plotted pairs. This line may be shown on the
XYPlot.

The best-fit line has the formula:

y = mx +b

Where m is the slope and b is the offset. To calculate m, we use the
following equation:

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