L4: QA-QC

Question 1

Quality

Answer 1

Features/characteristics of a product/service that meets needs and expectations

Question 1

Quality Assurance (QA)

Answer 1

system of activities (planning, assessment, quality improvement) to ensure that a process, item, or service reaches quality and expections

Question 2

Quality Control (QC)

Answer 2

measures attributes and performance of process, item, or service against standards to verify if they meet requirements (protection against out of control conditions and ensures results are of acceptable quality)

Question 3

Accuracy

Answer 3

measure of closeness of an individual measurement/avg number of measurements to the true value

Question 4

Assessment

Answer 4

evaluation of performance/effectiveness (audits, performance evaluation, management systems review, peer review, inspection)

Question 5

Audit (Quality)

Answer 5

examination that determines whether quality activities comply w/ planned arrangements and if they are effectives and suitable

Question 6

calibration

Answer 6

Comparing measurement standard, instrument, or item w/ a standard or instrument of higher accuracy to eliminate inaccuracies by adjustments

Question 7

Bias

Answer 7

Distortion of a measurement process that causes errors in one direction (measurement different from sample’s true value)

Question 8

What are three categories of bias?

Answer 8

constant, proportional, variable

Question 9

Comparability

Answer 9

measuring one data set to another with confidence

Question 10

Completeness

Answer 10

comparing valid data from measurement systems to expected data obtained under correct, normal conditions

Question 11

Confidence Interval

Answer 11

Numerical interval constructed around a point estimate of a population parameter, combined w/ probability statement linking it to the population’s true parameter value

Question 12

Detection Limit (DL)

Answer 12

measure of method capability to distinguish samples that don’t contain a specific analyte from samples w/ low concentrations of the analyte (analyte and matrix specific)

Question 13

Method

Answer 13

procedures/techniques to perform an activity (sampling, chemical analysis, quantification)

Question 14

Performance Evaluation (PE)

Answer 14

Type of audit where data is obtained independently and compared w/ routinely obtained data to evaluate the proficiency of an analyst/laboratory

Question 15

Precision

Answer 15

mutual agreement among individual measurements of sample property (similar conditions)

Question 16

Reproducibility

Answer 16

variability among measurements of sample sample at different laboratories

Question 17

Representativeness

Answer 17

describes how well your sample represents the environmental condition you are trying to measure

Question 18

Standard Operating Procedure (SOP)

Answer 18

document that details operation method, analysis, or action w/techniques and steps; officially approved as the method for performing routine/tasks

Question 19

Round Robin Study

Answer 19

different laboratories/analysts analyze the same sample w/same method; results are compared to develop new methods and see how reproducible it is

Question 20

Peer Review

Answer 20

Critical review of work conducted by qualified individuals to ensure activities are adequate, properly performed and documented, and meet quality requirements. Peer reviews provide evaluation of subjects where methods/measures of success are undefined (research, development)

Question 21

Data Quality Assessment (DQA)

Answer 21

scientific/statistical evaluation of data to determine if data obtained are of right type, quality, and quantity for intended use

Question 22

5 steps of DQA process

Answer 22

1. Review DQAs & sample design
2. conduct preliminary data review
3. select statistical test
4. verify assumptions of test
5. conclusions from data

Question 23

Data Quality Objectives (DQOs)

Answer 23

statements derived from DQO process. Defines data type and tolerable levels of decision errors

Question 24

Data Quality Objectives (DQO) Process

Answer 24

planning tool that identifies and defines type, quality, and quantity of data for specified use

Question 25

Data Quality Indicators (DQIs)

Answer 25

stats and qualitative descriptors that are used to interpret degree of acceptability of data utility to user (Bias, precision, accuracy, comparability, completeness, representativeness)

Question 26

What are two types of errors?

Answer 26

Systematic (reproducible/happens everytime, bias in process) & Random (non-reproducible, estimable)

Question 27

Measurement Errors

Answer 27

error due to measurement, calibration, and analysis (can be reduced but never eliminated)

Question 28

Detection Limit

Answer 28

when method can no longer detect a chemical as concentrations approach zero (more difficult to get accurate measurements)

Question 29

Can you write zero for instrumental measurement?

Answer 29

No, as for any instrumental measurement we only know that concentration is less than detection limit

Question 30

Sample Handling Errors

Answer 30

results from sample collection, transportation, and storage; can be minimized w/proper handling procedures

Question 31

Natural Variability

Answer 31

biggest source of imprecision (cannot be controlled), quantify this variability by taking more samples

Question 32

Rules to ensure accurate data through calibration:

Answer 32

use appropriate amount of standards (~3 & blank), generate calibration curves w/linear regression (use all pts), avoid data at extremes, know when to include a zero (include if instrument can read zero in blank and if its appropriate for colorimetric procedures), evaluate calibration accuracy (correlation coeff, calibration eq), defined calibration range.