Poisson Sampling


Book Description

"The prevailing assumption, that for Poisson sampling the adjusted estimator "Y-hat a" is always substantially more efficient than the unadjusted estimator "Y-hat u" , is shown to be incorrect. Some well known theoretical results are applicable since "Y-hat a" is a ratio-of-means estimator and "Y-hat u" a simple unbiased estimator. We formalize an additional realistic situation for high-value timber estimation for which "Y-hat u" is more efficient. (Please note: equations are spelled out inside quotation marks. Please see PDF for symbols.)"




Research Note RMRS


Book Description




Forest Measurements


Book Description

Harold Burkhart and Bronson Bullock have updated the quintessential introduction to forest measurements, providing a new generation of forestry students at all levels with the concepts and methods they need for career success. With attention to detail and clear, precise language, the authors present timber measurement techniques applicable to any tree inventory regardless of management objectives. Assuming no more mathematical background than algebra and plane trigonometry, the authors begin with basic statistical concepts to ensure that even introductory students benefit from the book’s concise explanations. Comprehensive coverage of sampling designs, land measurements, tree measurements, forest inventory field methods, and growth projections assures utility for foresters throughout their education and beyond. The new edition includes expanded discussions of information technology and geospatial information systems commonly employed in assessing forest resources. Recognizing the needs of contemporary forest inventories and models, a new chapter on assessing forest carbon builds on the foundations of traditional forest measurements, sampling, and modeling. Abundant photographs and illustrations highlight and clarify important concepts, while many numerical examples allow readers to become comfortable with the quantitative tools employed by foresters.




New Publications


Book Description




Forest Measurements


Book Description

Continuing a tradition of excellence spanning over forty years, the Fifth Edition of Forest Measurements supplies forestry students at all levels with the concepts and methods they need for future success. The authors present timber measurement techniques applicable to any tree inventory regardless of management objectives. Assuming only some background in algebra and plane trigonometry, basic statistical concepts are included, ensuring that even introductory students benefit from the book’s concise explanations. Thorough coverage of sampling designs, land measurements, tree measurements, forest inventory field methods, and growth projections ensures utility for foresters throughout their education and beyond. Chapters on aerial photographs and GIS introduce readers to these powerful measurement tools, and the concluding chapter expands the techniques discussed to encompass other natural resources such as rangelands, wildlife, and water. Exceptionally readable and clear, the book includes many photographs and illustrations, numerous numerical examples, and a bibliography to enhance the reader’s understanding of the material.




Sampling Methods


Book Description

Whenweagreedtoshareallofourpreparationofexercisesinsamplingtheory to create a book, we were not aware of the scope of the work. It was indeed necessary to compose the information, type out the compilations, standardise the notations and correct the drafts. It is fortunate that we have not yet measured the importance of this project, for this work probably would never have been attempted! In making available this collection of exercises, we hope to promote the teaching of sampling theory for which we wanted to emphasise its diversity. The exercises are at times purely theoretical while others are originally from real problems, enabling us to approach the sensitive matter of passing from theory to practice that so enriches survey statistics. The exercises that we present were used as educational material at the École Nationale de la Statistique et de l’Analyse de l’Information (ENSAI), where we had successively taught sampling theory. We are not the authors of all the exercises. In fact, some of them are due to Jean-Claude Deville and Laurent Wilms. We thank them for allowing us to reproduce their exercises. It is also possible that certain exercises had been initially conceived by an author that we have not identi?ed. Beyondthe contribution of our colleagues, and in all cases, we do not consider ourselves to be the lone authors of these exercises:they actually form part of a common heritagefrom ENSAI that has been enriched and improved due to questions from students and the work of all the demonstrators of the sampling course at ENSAI.




Regression and Other Stories


Book Description

A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.




Statistics with Confidence


Book Description

This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.




A Tutorial on Thompson Sampling


Book Description

The objective of this tutorial is to explain when, why, and how to apply Thompson sampling.




Trustworthy Online Controlled Experiments


Book Description

Getting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to • Use the scientific method to evaluate hypotheses using controlled experiments • Define key metrics and ideally an Overall Evaluation Criterion • Test for trustworthiness of the results and alert experimenters to violated assumptions • Build a scalable platform that lowers the marginal cost of experiments close to zero • Avoid pitfalls like carryover effects and Twyman's law • Understand how statistical issues play out in practice.