Sampling Methods for Applied Research: Text and Cases

Sampling Methods for Applied Research is an applied, one semester introduction to sampling methods for nonmathematics majors. Not just a handbook of formulas, this text uses simple numerical illustrations to provide an intuitive understanding of concepts and to confirm major results. In addition to the standard methods of sample selection and estimation, the book covers unequal probability sampling and the prediction approach.

Spis treści:
Part One: Text
∗ Introduction
∗ Preliminaries
∗ Simple random sampling
∗ Stratified random sampling
∗ Two–stage random sampling
∗ Ratio and regression estimators
∗ Some Special Topics
∗ Sampling with unequal probabilities
∗ Sampling from a process
∗ Nonsampling errors
Part Two: Cases
∗ Canabag Manufacturing Company–Part I
∗ Canabag Manufacturing Company–Part II
∗ Valuation of government properties–Part I
∗ Valuation of government properties–Part II
∗ Valuation of government properties–Part III
∗ Valuation of government properties–Part IV
∗ PackGoods Inc.
∗ Pharmacom Research–Part I
∗ Pharmacom Research–Part II
∗ Tenderdent Toothpaste
Appendices
∗ Basic Concepts
∗ Glossary and Technical Summary
∗ Computing Instructions
∗ Solutions to Selected Problems

Nota biograficzna:
About the Author Peter Tryfos is Professor of Management Science, Faculty of Administrative Studies, at York University, Ontario, Canada. He is the author of a text, Business Statistics, published in Canada by McGraw–Hill Ryerson, and a number of articles in applied statistics that have appeared in the Journal of the American Statistical Association, Management Science, Operations Research, and other journals.

Okładka tylna:
Sam pling Methods for Applied Research is an applied, one semester introduction to sampling methods for nonmathematics majors. Not just a handbook of formulas, this text uses simple numerical illustrations to provide an intuitive understanding of concepts and to confirm major results. In addition to the standard methods of sample selection and estimation, the book covers unequal probability sampling and the prediction approach.