Calibration Flashcards
What is quality assurance
Methods used to make sure the process is working and it up to a proper standard
What are the stages of data analysis when doing quality assurance
First you have raw data (your own measurements)
Then treated data (worked up data by finding concentrations and making a graph, might cut out some raw data)
Results (the final values and interpretations)
What are the steps to making a quality assurance prootocol
Set objectives (what are the goals, why are we analyzing, what do we need to know about the samples
Build specifications (what tests do you do, what min and max values do we want)
Make an assessment (stats, do the values agree with the specifications)
What do you include when trying tobuild specifications
You set a target value, min acceptable value, max acceptable value (tells the accuracy)
Max acceptable variance (tells the inconsistency in data)
What is a false postive
False negative
Test give “yes” value when actual sample should be no
Test give “no” value when actual sample should be yes
What is a blank sample
Sample with no analyte
Used to measure background signals/response
What is a reagent blank
A sample with all of the additional reagents (buffers, solvents) but still no analyte
Hasn’t been subjected to all preparation steps
What is a method blank
A reagent blank that’s also run through all of the processing steps (filtration, boiling, etc.)
Has everything except for analyte
What is a field blank
A method blank that is taken out into an environment that is similar to the analysis samples environment
What is a sample matrix
The rest of the sample (everything other than the analyte)
Can be simple like DI water or complex like ocean water
We need to account for the affects of the matrix components in blanks and the analysis solutions
What is a spike
- Identification: add more of the analyte to a sample and look for a change in response
- Spike recovery: adding known amount of analyte and seeing if the change in the signal is proportionate. If not, instrument might be faulty or the matrix could be in the way of the analysis
How do you makes sure you’re method of analysis is good?
Build a standard operating procedure and share it with other analysts
What is the error of selectivity
Give example
If the method of analysis responds to things other than the analyte
Ex. Measuring ph: ph electrodes respond to high [Na]
If low na then it’s fine
How do instruments respond to increasing analyte concentration
Linear response.
In terms of r^2 what is a good fit and what is a bad fit
1 is good
0 is bad
What do we want to see in residual plots
Scattered and random distributions of residuals
No patterns
What are methods to use to know if the value we measured is “true” and not just reproducible and wrong
Test the sample against a standard reference material (that been pre analyzed by trusted labs like NIST)
Test it against analysis done by another (trusted) lab (by sending it to that lab)
Test it against another trusted method (use an old method, spike recovery)
Test it with internal standards, standard addition, and spike recovery (to see if matrix or sample prep affect your method)
What are the two thing included precision and what do they mean
Reproducibility: repeating your own data, similar trial to trial or day to day
Repeatability: the similarity of results between different analysts or labs (other people repeating your values)