General Statistical Design and Analysis for Laboratory Decisions [Foundation Course, 4 days]
 

I. BASIC STATISTICS AND STATGRAPHICS
A. Context of Statistical Thinking: Preliminary Concepts
B. STATGRAPHICS Fundamentals
C. Basic Sample Statistics: Numeric and Graphical Portrayals


II. FRAMEWORK FOR STATISTICAL THINKING
A. Context of Statistical Thinking: The Decision Environment
B. The Inference Cycle: Foundations of the Framework
C. Repeated Sampling from the Real World: Concept of Sampling Distributions
D. Uncertainty: Concepts and Measures
E. Paradigms of the Framework, ie:
Repeatability and Equipment Precision
Estimating Concentrations
Comparison to Standards
 
III. FRAMEWORK FOR LABORATORY STATISTICS
A. Decision Context
B. Laboratory Measurement Process
C. Laboratory Quality Assurance
D. Evaluation of Analytical Methods
E. Implications for Laboratory Statistics


IV. SYSTEMATIC ERROR AND BIAS
A. Concepts: Fixed and Relative Bias
B. Fixed Bias
C. Relative Bias


V. RANDOM ERROR AND PRECISION
A. Concepts and Inferences
B. Relative Precision and Weighted Regression


VI. CALIBRATION OF MEASUREMENT METHODS
A. Modeling the Calibration Problem
B. Using the Calibration Model: Estimation of Unknown Concentration
C. Strategies for Increasing Precision of the Estimate
D. Method of Standard Additions
E. General Calibration Curves


VII. SENSITIVITY: LOD AND LOQ DETECTION CRITERIA
A. Concepts and Estimation
B. Applicability and Implications for Data Use and Interpretation