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About Positive and Negative of Deviation Data
The deviation data detected when Detect Mode is
"Measure Deviation" is positive or negative
depending on the scan direction (of the cell). When
the scan direction (upper dashed arrow) is from left
to right, the right area across the approximate line
is positive and left area is negative as the right
figure
When the scan direction is the other way, the
positive and negative areas are also inverted.
What are Maximum, Minimum and Average Measurement
Values?
Calculates the deviation, distance or width using the edges detected by each cell. Then, calculates the
maximum, minimum and average values for the remaining data except the data judged as noises.
The criterion to judge data as noises is decided by "Denoising" function.
As the graph displayed on the screen (described below) shows the maximum and minimum values before
denoising, the values of the graph may be different from the output values.
About Denoising function: page 195
What is Standard Deviation?
It is the value that the variation in values of
deviation, distance or width is quantified. It is
calculated by the formula mentioned on the right.
The larger value indicates the greater variation.
The right formula is for the case of "Detect mode:
Measure Distance". For the case of "Measure
Deviation" or "Measure Width", replace the
"Distance" in the right formula with "Deviation" or
"Width".
What is Linearity?
Linearity is the difference between the maximum and minimum values of
the deviation for an approximate line.
In case of the "Measure Distance" mode and "Measure Width" mode,
linearity is also calculated in the same method as the "Measure Deviation"
mode.
188
The calculation method for "Standard Deviation" used for
Denoising function is different.
Linearity
Approximate
line
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