Christopher Z. Mooney is a professor of political studies with a joint appointment in the Institute of Government and Public Affairs. Mooney studies U.S. state politics and policy, with special focus on legislative decision making, morality policy, and legislative term limits. He is the founding editor of State Politics and Policy Quarterly, the premier academic journal in its field and has published dozens of articles and books, including Lobbying Illinois - How You Can Make a Difference in Public Policy. Prior to arriving at UIS in 1999, he taught at West Virginia University and the University of Essex in the United Kingdom
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Description
PART ONE: INTRODUCTION Traditional Parametric Statistical Inference Bootstrap Statistical Inference Bootstrapping a Regression Model Theoretical Justification The Jackknife Monte Carlo Evaluation of the Bootstrap PART TWO: STATISTICAL INFERENCE USING THE BOOTSTRAP Bias Estimation Bootstrap Confidence Intervals PART THREE: APPLICATIONS OF BOOTSTRAP CONFIDENCE INTERVALS Confidence Intervals for Statistics With Unknown Sampling Distributions Inference When Traditional Distributional Assumptions Are Violated PART FOUR: CONCLUSION Future Work Limitations of the Bootstrap Concluding Remarks