The Calibration module is most useful for analytical laboratories and metrological departments. It contains linear and nonlinear calibration models. Automatic detection of departures from linearity can be requested. Due to the fact that the module implements weighted regression, it can be successfully used for models with heteroscedastic errors. This feature can be useful namely for analyzing low-level measurement data (e.g. trace analysis).

Calibration - Pdf manual

Calibration data example:

X	Y	Sample	Repl1	Repl2	Repl3
1.281	25.53	No.1	33.69	33.74	33.73
1.281	25.58	No.2	39.25	39.25	39.27
2.558	51.37	No.3	50.6
2.558	51.23	No.4	57.3
5.430	106.4
5.430	108.7
7.373	148.4
7.373	146.6
11.59	233

Input panel

Different methods to determine detection limit

Interactive calibration plot with zoom feature

InteractiveCalibration calculator

Other diagnostic plots

Sample Text output:

Calibration
Task name :	Sheet36
Data size:	17
Significance level :	0.05
Choice of calibration model :	Automatic
Used calibration model :	Linear
Suitability of the model :	Model is correct
Weighted regression used :	Yes
Parameters of calibration model
Parameter	Estimate	St. deviation	C.I. Lower	C.I. Upper
Abs.	0.035973483	0.018686223	-0.003855259	0.075802226
X	1.000345445	0.006698099	0.986068785	1.014622106
Absolute term significance
Value	C.I. Lower	C.I. Upper	Conclusion
0.035973483	-0.003855259	0.075802226	Insignificant
Validation of slope
Value	C.I. Lower	C.I. Upper	Slope=1
1.000345445	0.986068785	1.014622106	Yes
Sensitivity of the model :	1.000345445
Chosen factor K :	3
Computed Blank signal std. deviation :	0.104747028
Analysis of residuals
Residual sum of squares :	0.164579099
Average absolute residual :	0.069216963
Correlation coefficient :	0.999523393
Index	Measured X	Measured Y	Computed Y	Weight
1	0.31	0.38	0.351042915	12.24674589
2	1.31	1.30	1.343511625	11.9160705
3	1.56	1.58	1.59556717	11.70231418
4	1.56	1.58	1.59556717	11.70231418
5	2.52	2.53	2.556528936	9.915347572
6	2.65	2.72	2.682556709	9.536528779
7	2.66	2.72	2.69831018	9.486749624
8	4.39	4.44	4.431192054	3.194978968
9	4.54	4.61	4.572973298	2.83820524
10	4.58	4.66	4.620233713	2.728207814
11	7.64	7.73	7.6764072	0.527537807
12	7.64	7.73	7.6764072	0.527537807
13	7.65	7.59	7.692160671	0.52572007
14	7.70	7.97	7.739421086	0.520396645
15	9.86	9.79	9.897646693	0.388805078
16	9.86	9.79	9.897646693	0.388805078
17	9.81	9.60	9.850386278	0.390380962

One of the methods to estimate detection limits