Zum Hauptinhalt springen
Nicht aus der Schweiz? Besuchen Sie lehmanns.de
Introduction to the Laws of Statistical Sampling - Bernard Grofman

Introduction to the Laws of Statistical Sampling

With Illustrations From Election Polling

(Autor)

Buch | Softcover
144 Seiten
2025
SAGE Publications Inc (Verlag)
979-8-3488-3230-8 (ISBN)
CHF 67,95 inkl. MwSt
A concise, intuitive monograph that demystifies statistical sampling theory—especially as applied to elections and survey research—using real-world examples, simulations, and Excel-based tools. It’s designed to be accessible to readers with only high school algebra.

Bernard Grofman is Distinguished Research Professor of Political Science and Social Psychology, School of Social Sciences, University of California, Irvine. A member of the American Academy of Arts and Science, he was the inaugural Jack W. Peltason Endowed Chair of Democracy Studies at UCI and has also been an Adjunct Professor of Economics at UCI and a visiting scholar-in-residence at universities in nearly a dozen countries.

Series Editor Introduction
Acknowledgements
About the Author
Chapter 1: An Overview
1.1 Distinctive Features of the Approach to Sampling and Inference in This Volume
1.2 The Structure of this Book
1.3 Notation
1.4 Basic Metrics
APPENDIX to Chapter 1: A Few Useful EXCEL Functions and Tools
Chapter 2: Sampling Distributions
2.1 Ideal Types of Univariate Data Distributions
2.2 The Normal Distribution and the Standardized Normal Distribution
2.3 Approximately Normal Distributions
2.4 Cumulative Distributions and Finding Percentile Ranks Using EXCEL
2.5 The Binomial Distribution
2.6 The t-Distribution
2.7 Other Approximately Normal Distributions
2.8 Skewness and Kurtosis
2.9 Not all Univariate Distributions are Approximately Normal
APPENDIX to Chapter 2: Theorem Proofs
Chapter 3: Sampling and Hypothesis Testing
3.1 Sampling and Hypothesis Testing
3.2 An Inventory of the Ten Laws of Statistical Sampling
3.3 Sampling From a Normal Distribution with Binomial Variance
APPENDIX to Chapter 3: Distinguishing the Standard Error of the Mean From the Sample Error
Chapter 4: Using EXCEL to Answer the First Five of our Six Questions
4.1 Five Paradigmatic Questions About Sampling in Two-Candidate Elections
Chapter 5: Difference of Means
5.1 Question 6. “When can we reject the claim that two distributions are drawn from the same population?”
5.2 Experiments as the Basis for Generating Data for a Difference of Means Test
5.3 Statistical Significance versus Substantive Significance: The Importance of Sample Size
5.4 Illustrating Ideological Polarization and Partisan Sorting with Polling Data
5.5 Warnings about Causation and Selection Bias Effects
Chapter 6: Unifying Perspectives on Sampling and Hypothesis Testing Involving a Univariate Distribution
6.1 Similarities Across Statistical Tools
6.2 Concluding Thoughts
APPENDIX 1 to Chapter 6 - Parallels Between the Ideas in this Book and Regression Analysis
APPENDIX 2 to Chapter 6: A Short List of Suggestions for Further Reading
References
Index

Erscheinungsdatum
Reihe/Serie Quantitative Applications in the Social Sciences
Verlagsort Thousand Oaks
Sprache englisch
Maße 139 x 215 mm
Gewicht 180 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Sozialwissenschaften Politik / Verwaltung Politische Theorie
Sozialwissenschaften Soziologie Empirische Sozialforschung
ISBN-13 979-8-3488-3230-8 / 9798348832308
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
eine Einführung mit Python, Scikit-Learn und TensorFlow

von Oliver Zeigermann; Chi Nhan Nguyen

Buch | Softcover (2024)
O'Reilly (Verlag)
CHF 27,85
Von den Grundlagen bis zum Produktiveinsatz

von Anatoly Zelenin; Alexander Kropp

Buch (2025)
Hanser (Verlag)
CHF 69,95