How to apply uncertainty analysis to experimentation. Describes how to incorporate uncertainty analysis into the planning, design, construction, debugging, execution, data analysis, and reporting stages of experimental programs. Estimation and propagation of both precision (random) errors and bias (fixed) errors are considered, as are procedures for handling small samples (which require use of the t -distribution), and practical cases in which bias...