Title
Bootstrapping: A Nonparametric Approach To Statistical Inference (Quantitative Applications In The Social Sciences),New
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Bootstrapping, a computational nonparametric technique for 'resampling,' enables researchers to draw a conclusion about the characteristics of a population strictly from the existing sample rather than by making parametric assumptions about the estimator. Using real data examples from per capita personal income to median preference differences between legislative committee members and the entire legislature, Mooney and Duval discuss how to apply bootstrapping when the underlying sampling distribution of the statistics cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, they show the advantages and limitations of four bootstrap confidence interval methods: normal approximation, percenti
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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
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We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the focus of the book 'Bootstrapping: A Nonparametric Approach to Statistical Inference'? A: The book focuses on bootstrapping, a computational nonparametric technique used for re-sampling to draw conclusions about population characteristics from existing samples without making parametric assumptions.
- Q: Who are the authors of this book? A: The authors of the book are Christopher Z. Mooney and David A. Duval.
- Q: What topics are covered in this book? A: The book covers the application of bootstrapping techniques, advantages and limitations of various bootstrap confidence interval methods, and real data examples from social sciences.
- Q: What is the publication date of the book? A: The book was published on August 9, 1993.
- Q: Is this book suitable for beginners in statistics? A: While the book addresses complex statistical concepts, it is designed for researchers and may require some prior knowledge of statistical methods to fully comprehend its content.
- Q: How many pages does the book contain? A: The book contains 80 pages.
- Q: What is the binding type of the book? A: The book is available in paperback binding.
- Q: Are there practical examples included in the book? A: Yes, the book includes real data examples, making it practical for understanding bootstrapping applications.
- Q: Does the book discuss the limitations of bootstrapping methods? A: Yes, the authors discuss both the advantages and limitations of four different bootstrap confidence interval methods.
- Q: What category does this book fall under? A: The book falls under the category of Probability & Statistics.