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The samples and the Error
Chap 1. The samples and the Error
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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
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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
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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
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Seven steps of the sample’s life Sample ; easy to destruct by air, light etc. house for living things also.
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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
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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
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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
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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
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