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This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

The Coding Manual for Qualitative Researchers is unique in providing, in one volume, an in-depth guide to each of the multiple approaches available for coding qualitative data. In total, 29 different approaches to coding are covered, ranging in complexity from beginner to advanced level and covering the full range of types of qualitative data from interview transcripts to field notes. For each approach profiled, Johnny Saldaña discusses the method’s origins in the professional literature, a description of the method, recommendations for practical applications, and a clearly illustrated example.

"The Guide to GPS Positioning is a self-contained introduction to the Global Positioning System, designed to be used in any of the following three ways: as a self-study guide, as lecture notes for formal post-secondary education courses, or as hand-out material to support short-course and seminar presentations on GPS." -- Introduction.

This publication shows readers how to design and conduct a census or sample survey. It explains basic survey concepts and provides information on how to create efficient and high quality surveys. It is aimed at those involved in planning, conducting or managing a survey and at students of survey design courses. This book contains the following information: formulating the survey objectives and design a questionnaire; things to consider when designing a survey (choosing between a sample or a census, defining the survey population, choosing which survey frame to use, possible sources of survey error); determining the sample size, allocate the sample across strata and select the sample; appropriate uses of survey data and methods of point and variance estimation in data analysis; data dissemination and disclosure control; using administrative data, particularly during the design and estimation phases; choosing a collection method (self-enumeration, personal interview or telephone interview, computer-assisted versus paper-based questionnaires); organizing and conducting data collection operations; processing data (all data handling activities between collection and estimation) and using quality control and quality assurance measures to minimize and control errors during various survey steps; and planning and managing a survey. This publication also includes a case study that illustrates the steps in developing a household survey, using the methods and principles presented in the book.

Exact algorithms for dealing with geometric objects are complicated, hard to implement in practice, and slow. Over the last 20 years a theory of geometric approximation algorithms has emerged. These algorithms tend to be simple, fast, and more robust than their exact counterparts. This book is the first to cover geometric approximation algorithms in detail. In addition, more traditional computational geometry techniques that are widely used in developing such algorithms, like sampling, linear programming, etc., are also surveyed. Other topics covered include approximate nearest-neighbor search, shape approximation, coresets, dimension reduction, and embeddings. The topics covered are relatively independent and are supplemented by exercises. Close to 200 color figures are included in the text to illustrate proofs and ideas.