Linear regression by least squares – Rockwell Automation FactoryTalk Historian SE ProcessBook 3.2 User Guide User Manual
Page 168
●
●
●
●
●
FactoryTalk Historian ProcessBook User Guide
150
<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: