Quality Assurance and Calibration Methods

These flashcards cover key concepts from the lecture on quality assurance and calibration methods in analytical chemistry.

What is the purpose of quality assurance in analytical chemistry?

To ensure the accuracy and precision of measurements to support reliable decisions.

What are the three types of data discussed in the lecture?

Raw data, treated data, and final reported results.

What does a method blank diagnose?

It detects contamination, carryover, and systematic bias in the analytical process.

What is a use objective?

A statement that explains why data are needed and how the results will be used.

What is the purpose of calibration checks?

To test whether the instrument continues to perform accurately after initial calibration.

What does specificity refer to in method validation?

The ability of a method to respond to the analyte and not to coexisting substances.

Define linearity in the context of calibration curves.

Linearity indicates that the response of the method is proportional to analyte amount over the working range.

What is a false positive in analytical testing?

It is when a test indicates the presence of an analyte above a limit when it is not actually present.

What is meant by detection limit (DL)?

The lowest concentration of an analyte that can be reliably detected but not necessarily quantified.

What is standard addition used for?

To correct for matrix effects by adding known amounts of analyte directly to the unknown sample.

How are internal standards beneficial in analytical chemistry?

They provide a way to compensate for variability in instrument response and sample preparation.

What is the meaning of robustness in method validation?

Robustness refers to the method's ability to remain acceptable under small deliberate variations in conditions.

What does a control chart help identify?

It helps detect shifts in the process and variations affecting accuracy, precision, or drift.

What computation is used to assess spike recovery?

% recovery = (Cspiked sample - Cunspiked sample) / Cadded x 100.

Why is it important to verify linearity and range during calibration?

To ensure the calibration method provides accurate and reliable results across expected concentrations.

What factors determine acceptable performance specifications?

Sampling requirements, accuracy, precision, selectivity, sensitivity, detection limit, and acceptable blank values.