Standard Curve Calculator
Generate a standard curve from absorbance data using linear or quadratic regression fitting. Supports replicate averaging, blank subtraction, and unknown sample interpolation for BCA, Bradford, and any colorimetric assay.
Standard Data
📋 Paste from spreadsheet
| ✓ | Conc. | Rep 1 | Rep 2 | Rep 3 |
|---|
Unknown Samples
📋 Paste from spreadsheet
| Name | Rep 1 | Rep 2 | Rep 3 | Dilution Factor |
|---|
How Standard Curve Fitting Works
A standard curve (also called a calibration curve) establishes the relationship between a known concentration and a measured signal (typically absorbance). By measuring a series of standards with known concentrations, you can fit a mathematical model to the data and use it to determine the concentration of unknown samples from their absorbance readings.
This calculator supports linear regression (y = mx + b) for assays within their linear range, and quadratic fitting (y = ax² + bx + c) for extended ranges where the relationship is slightly curved. The fit quality is assessed by the coefficient of determination (R²), where values closer to 1.0 indicate better fit.
Replicate Measurements and Statistical Confidence
Running duplicate or triplicate measurements for each standard and unknown sample improves the reliability of your standard curve. This calculator computes the mean, standard deviation (SD), and coefficient of variation (CV%) for each point. A CV% above 20% is flagged as high variability, indicating that the measurement should be repeated or the outlier investigated.
Individual replicate values are shown on the chart alongside the mean, providing a visual assessment of measurement precision at each concentration level.
Blank Subtraction
The blank (0 concentration) standard represents the background signal from the reagent alone. In Auto mode, this calculator subtracts the mean blank absorbance from all data points before fitting. If you have already performed blank subtraction on your data, switch to None mode. When no blank (0 concentration) row is present, blank subtraction is automatically skipped.
ℹ️ Frequently Asked Questions
When should I use linear vs quadratic fitting?
Use linear fitting when your standards are within the assay's linear range (most common for BCA and Bradford). If R² drops below 0.99 with linear fitting, or if you are using an extended concentration range, try quadratic fitting. A good quadratic fit will have R² > 0.995 and a small quadratic coefficient (a).
What does "extrapolation" mean and why is it warned?
Extrapolation occurs when an unknown sample's absorbance falls outside the range covered by your standard points. The calculated concentration is based on extending the curve beyond measured data, which is unreliable. Dilute (or concentrate) your sample so that its absorbance falls within the standard range.
How do I handle outlier standard points?
Click the checkbox next to any standard point to exclude it from the fitting. The excluded point will appear grayed out on the chart with an × marker. The curve and R² will be recalculated using only the included points. Document which points you excluded and why in your lab notebook.
What R² value is acceptable?
For most colorimetric protein assays, R² ≥ 0.99 is considered acceptable. Below 0.98, the curve may not be reliable for accurate quantification. Check for pipetting errors, expired reagents, or standards that are outside the assay's working range.
What is the dilution factor?
If you diluted your sample before measurement (e.g., 1:5 dilution), enter 5 as the dilution factor. The calculator will multiply the curve-derived concentration by this factor to give the original sample concentration. A dilution factor of 1 means no dilution was performed.