Excel Calibration Curve Video TutorialWorking in the laboratory, there are a number of different ways that we can calculate the amount of an analyte present in a sample by comparing them to standards. You could use a single external standard, a calibration curve, internal standard or use standard addition. Learning to use these different methods of calculation is essential to working in the laboratory and is a essential part of any laboratory training program.
This is a video tutorial for making an Excel sheet to create a calibration curve using six standards and using it to automatically back calculating unknown sample concentrations.
The sheet also includes a dilutions factor calculator using which the concentration of analyte in the undiluted samples can also be automatically calculated.
We also show you how to protect the Excel sheet so that the formulas cannot be altered by mistake and also you can further validate the Excel sheet for use in a regulated environment.
For best results see the video in HD, in full screen mode and use headphones for better sound clarity.
From the video tutorial you will learn how to –
- Enter data for a calibration curve in excel
- Make a calibration curve with linear regression trend line
- Display the linear regression equation of the line on the graph
- Display r2 value of the regression line on the graph
- Calculate the slope and intercept for the regression line using formulas
- Calculate the concentration of unknown samples using the equation y = mx + c
- Calculate dilution factor for samples which are diluted prior to analysis
- Calculate undiluted sample concentrations
- Protecting the excel sheet so you can validate it in the future
- Formatting the excel sheet so it can be printed properly on one sheet of paper
What can you use this sheet for?
You can use this sheet for calculating sample concentration from a standard calibration curve for any technique like HPLC, GC, UV, AAS or any other technique where linear regression is used. You can also use it in method validation to evaluate linearity of the response and establish the range of the method.
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