1. The samples and the Error
Chap 1.
The samples and the Error

2. The importance of reliable and legally defensible data
Correct sampling and analytical protocol, Good laboratory practice (GLP), Correct test results
Components of legally defensible data
- custody or control
chain of custody ; able to identify all persons who had possession of the sample for all period of time
control ; placed in a designated secure area, possessed by investigator’s or transferre’s
- documentation
- Traceability ; which reagent and standard were used and their origin
 Tip ; Need a lab notebook, do not remove any pages and erase previous writing

3. Sampling error vs Analytical error
Determinative error (systemic error), Indeterminate error(random error)
Errors can be minimized through the proper design and implementation of a quality program
QC (quality control) ; system of technical activities aimed at controlling the quality of data
QA (quality assurance); management system that ensures the QC is working as intended

4. Three phases of data collection process (EPA) – 7 major tasks
O Planning
1.DQOs (data quality objectives development) ; sampling design
2. SAP (sampling and analysis plan preparation) ; type, quantity, quality
Together with field QA/QC
O Implementation
3. Sampling and filed data collection
4. Laboratory analysis
5. Filed and laboratory QA/QC
O Assessment
6. Data evaluation,
7. Data quality assessment

5. Seven steps of the sample’s life Sample ; easy to destruct by air, light etc. house for living things also.

6. Total error and its sources
; combination of various errors that occur during sampling, analysis and in data management. controllable and minimize total error .
-Sampling error ; planning and implementation phase
- non-sampling error ; implementation and assessment phase
o Some errors can be manageable but the most damaging errors are hidden

7. The sources of sampling error
 Quantifiable components ; can be evaluated by statistically and controlled through the application of appropriate sampling design
-Errors originating from inherent sample variability ; sample itself (ex; soil)
-Errors originating from population variability (by random selection)
Can be evaluated statistically and controlled through appropriate sampling design
 Qualitative factors ; planning processes and the implementation of field procedure
-Sampling design error
-Field procedure error

8. Non-sampling error O Laboratory error
- measurement (can be controlled by QC protocol)
- data interpretation error
- sample management error; improper storage, mislabel, cross contamination etc
- laboratory procedure error ; unproper analysis procedure
- Methodology error; non standard, unproven analytical method
O Data management error
; incorrect computer program, record keeping, lack of attention etc

9. O Qualitative error >> Quantifiable error
O Can evaluate the total errors by Data quality indicators(DQI)
- A group of quantitative and qualitative descriptors, namely
Precision, Accuracy, Representativeness, Comparability, Completeness (PARCC parameter ; principal DQIs)
The EPA gives acceptance criteria to decide meaningful PARCC parameters
O Acceptance criteria ; Specified limits placed on characteristic of an item, process, or service defined in requirements document