Download Q-test for Rejection of Outliers

Q-test for Rejection of Outliers
Introduction
The Q-test is a simple statistical test to determine if a data point that is very different
from the other data points in a set can be rejected. Only one data point may be discarded
using the Q-test.
Q = |outlier - value closest to the outlier| / |highest value - lowest value|
Table of Q critical values (90% confidence)
N
3
4
5
6
7
8
9
10
QC
0.94
0.76
0.64
0.56
0.51
0.47
0.44
0.41
If Q is larger than QC the outlier can be discarded with 90% confidence
Linear Regression
Introduction
Linear regression uses the method of least squares to determine the best equation
describing a set of x and y data points.
Linear Regression Equations
For the equation y = mx + b
Useful quantities:
Slope:
Intercept:
Standard deviation of the residuals:
Standard deviation of the intercept:
Standard deviation of the slope:
Standard deviation of a unknown read from a calibration curve:
Where:
N is the number of calibration data points.
L is the number of replicate measurements of the unknown
and yc (bar) is the mean of the unknown measurements