Course Outline

Introduction to Sampling Theory

• The steps of the Sample Quality Criteria (SQC) process
• Difficulties in implementing the SQC process
• The three most important questions in a sampling campaign
  • What is the question?
  • What s the Decision Unit?
  • What is the confidence required?

Measuring and Mitigating Sampling Errors

• Material properties
  • Finite
  • Infinite
• Types of heterogeneity
  • Compositional heterogeneity
  • Distributional heterogeneity
• Major sampling errors
  • Fundamental error
  • Grouping and segregation error
  • Materialization error

Selection and use of Sampling Tools

• Commonly used sampling tools
• Which sampling tools cause bias and why
• How improper use of sampling tools causes bias
• The correct use and design of sampling tools

Statistics for Sampling

• Definition and types of statistics
• Definition of bias and variability
• Why variability is a concern
• How sampling and variability are related
• How sampling and bias are related
• How sampling affects statistical analysis
• Inference
• Confidence intervals

Field Quality Control

• Types of quality control field samples
• Interpretation of quality control results
• How to properly take splits and replicates
• Resampling and outliers

Sampling Protocol Development

• Developing sampling protocols
• Evaluating sampling protocols to meet SQC
• Standardizing sampling protocols
• Probabilistic vs non-probabilistic sample selection
• Choosing sampling locations
• Modes of sample selection
  • Simple random
  • Stratified random
  • Systematic random

Cost Effective Sampling

• Grab/discrete and composite samples
• MULTI INCREMENT samples
• Using historical data to estimate required sampling approach
• Field analytical methods