### 5 assays found tagged with weighting

Quantitative analysis of samples using a Four Parameter Logistic Fit (4PL) with x^{2} weighting. The applied weighting is used to offset heteroscedasticity by taking into account the change in variance which occurs with an increase in concentration. All samples are first corrected by the mean of the blank group measurements. The standard data points are plotted (concentration vs. corrected measurement) and a Four Parameter Logistic Fit (4PL) with x^{2} weighting is made through these points. The concentrations of the unknown samples are determined from the fit. It is important to note that concentrations can only be determined for samples which fall within the range of the determined upper and lower asymptotes of the fit (the a and d parameters).

Quantitative analysis of samples using a Four Parameter Logistic Fit (4PL) with 1/y weighting. The applied weighting is used to offset heteroscedasticity by taking into account the change in variance which occurs with an increase in signal. All samples are first corrected by the mean of the blank group measurements. The standard data points are plotted (concentration vs. corrected measurement) and a Four Parameter Logistic Fit (4PL) with 1/y weighting is made through these points. The concentrations of the unknown samples are determined from the fit. It is important to note that concentrations can only be determined for samples which fall within the range of the determined upper and lower asymptotes of the fit (the a and d parameters).

Quantitative analysis of samples using a Four Parameter Logistic Fit (4PL) with 1/y^{2} weighting weighting. The applied weighting is used to offset heteroscedasticity by taking into account the change in variance which occurs with an increase in signal. All samples are first corrected by the mean of the blank group measurements. The standard data points are plotted (concentration vs. corrected measurement) and a Four Parameter Logistic Fit (4PL) with 1/y^{2} weighting is made through these points. The concentrations of the unknown samples are determined from the fit. It is important to note that concentrations can only be determined for samples which fall within the range of the determined upper and lower asymptotes of the fit (the a and d parameters).

Quantitative analysis of samples using a Five Parameter Logistic (5PL) curve fit suitable for calculating concentrations from symmetrical sigmoidal calibrators. Data points are weighted using the expresson 1/y meaning that points with a lower signal have a higher weight. This analysis optionally includes a background correction step. If a blank group is included on your layout, the mean of the blank replicates is first subtracted from the raw data measurements (the corrected values are then used in the fit). The standard data points (concentration vs. measurement) are plotted on semi-log axes and a 5PL is made through the points. The concentrations of the samples are determined from the fit with any specified dilution factors applied. The %CV, Standard Deviation and Standard Error are calculated for each replicated sample. Samples outside the range of the standards or the fit (greater than the upper asymptote or below than the lower asymptote) are highlighted in yellow.

Quantitative analysis of samples using a Five Parameter Logistic (5PL) curve fit suitable for calculating concentrations from symmetrical sigmoidal calibrators. Data points are weighted using the expresson 1/y² meaning that points with a lower signal have a higher weight. This analysis optionally includes a background correction step. If a blank group is included on your layout, the mean of the blank replicates is first subtracted from the raw data measurements (the corrected values are then used in the fit). The standard data points (concentration vs. measurement) are plotted on semi-log axes and a 5PL is made through the points. The concentrations of the samples are determined from the fit with any specified dilution factors applied. The %CV, Standard Deviation and Standard Error are calculated for each replicated sample. Samples outside the range of the standards or the fit (greater than the upper asymptote or below than the lower asymptote) are highlighted in yellow.