Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.
Table of Contents
Overview of Different Types of Statistical
Constructing Statistical Intervals Assuming a
Normal Distribution Using Simple Tabulations.
Methods for Calculating Statistical Intervals
for a Normal Distribution.
Distribution-Free Statistical Intervals.
Statistical Intervals for Proportions and
Percentages (Binomial Distribution).
Statistical Intervals for the Number of
Occurrences (Poisson Distribution).
Sample Size Requirements for Confidence
Intervals on Population Parameters.
Sample Size Requirements for Tolerance
Intervals, Tolerance Bounds, and
Sample Size Requirements for Prediction
A Review of Other Statistical Intervals.
Other Methods for Setting Statistical