Statistical Data Analysis Explained

Applied Environmental Statistics with R

Author: Clemens Reimann,Peter Filzmoser,Robert Garrett,Rudolf Dutter

Publisher: John Wiley & Sons

ISBN: 1119965284

Category: Science

Page: 362

View: 5472

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.

Einführung in Statistik und Messwertanalyse für Physiker


Author: G. Bohm,G. Zech

Publisher: N.A

ISBN: 9783540257592


Page: 400

View: 1119

Die Einf]hrung in die Statistik und Messwertanalyse f]r Physiker richtet sich weniger an mathematischen \berlegungen aus, sondern stellt die praktische Anwendung in den Vordergrund und schdrft die Intuition experimentelle Ergebnisse richtig einzuschdtzen. Zahlreiche ausf]hrlich betrachtete Beispiele dienen dazu, hdufig bei der Datenanalyse gemachte Fehler zu vermeiden (unsinnige Anwendung des Chi-Quadrattests, Funktionenanpassung bei falscher Parametrisierung, Entfaltung mit willk]rlicher Regularisierung). Ein besonderes Augenmerk wird auf den Vergleich von Daten mit Monte-Carlo-Simulationen gelenkt. Moderne Experimente kommen nicht ohne Simulation aus. Deshalb ist es wichtig zu wissen, wie Parameteranpassungen und Entfaltungen in diesem Fall durchgef]rt werden. Au_erdem werden den Studierenden moderne Entwicklungen der Statistik nahegebracht, die in dlteren Lehrb]chern nicht behandelt werden.

Geographical Data Analysis

Author: Nigel Walford

Publisher: John Wiley & Sons Incorporated


Category: Business & Economics

Page: 446

View: 6301

It is increasingly important for the earth science student to appreciate that the acquisition of skills in statistics and computerised data analysis is as much part of modern geography as work in the field, laboratory or library. In this respect, Geographical Data Analysis aims to link the use of statistical techniques by means of computer software, to the acquisition of geographical-knowledge and the scientific method of enquiry. The book has three objectives: to explain basic statistical techniques and demonstrate their application to quantitative geography; to equip students with the knowledge and skills necessary for carrying out research projects; and to make the link between statistical analysis and the substantive topics taught as part of a geography course. An important innovative feature of the book is its project-orientated approach, which utilises exemplar projects drawn from human and physical geography. Each exemplar project shows the progress from the conception of the initial research through to the formulation of tentative hypotheses and the subsequent statistical analysis. The projects exemplify both primary and secondary methods for collecting geographical data, with the computer-based application of a wide range of statistical techniques. Thus, these projects allow discussion of sample design, data collection and computerisation, and a selection of appropriate statistical techniques. As such, Geographical Data Analysis integrates quantitative and geographical methodologies and provides a thorough understanding of basic statistical techniques for the undergraduate geography student; it will be of use from first year through to final degree dissertations.

A Casebook for Spatial Statistical Data Analysis

A Compilation of Analyses of Different Thematic Data Sets

Author: Daniel A. Griffith,Larry J. Layne,J. K. Ord,Akio Sone

Publisher: Oxford University Press on Demand

ISBN: 0195109589

Category: Mathematics

Page: 506

View: 7876

This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallels between geostatistical and spatial autoregressive findings. Both SAS and SPSS code are presented for implementation purposes. This informative casebook will serve geographers, regional scientists, applied spatial statisticians, and spatial scientists from across disciplines.

Introduction to Statistical Data Analysis for the Life Sciences

Author: Claus Thorn Ekstrom,Helle Sørensen

Publisher: CRC Press

ISBN: 1482238942

Category: Mathematics

Page: 526

View: 3324

A Hands-On Approach to Teaching Introductory Statistics Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets. New to the Second Edition A new chapter on non-linear regression models A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken Additional exercises in most chapters A summary of statistical formulas related to the specific designs used to teach the statistical concepts This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.


Concepts and Applications for Science

Author: David C. LeBlanc

Publisher: Jones & Bartlett Learning

ISBN: 9780763722203

Category: Statistics

Page: 382

View: 7749

Workbook to accompany - ( ISBN 0763722200).

Advanced Quantitative Data Analysis

Author: Cramer, Duncan

Publisher: McGraw-Hill Education (UK)

ISBN: 0335200591

Category: Social Science

Page: 254

View: 6634

There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. The following features characterize this book: concise and accessible introduction to calculating and interpreting advanced statistical techniques; use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique; succinct illustration of writing up the results of these analyses; minimum of mathematical, statistical and technical notation; annotated bibliography and glossary of key concepts.

Understanding Nursing Research

Building an Evidence-Based Practice

Author: Susan K. Grove,Jennifer R. Gray,Nancy Burns

Publisher: Elsevier Health Sciences

ISBN: 0323293328

Category: Medical

Page: 544

View: 3889

As the bestselling nursing research text, Understanding Nursing Research: Building an Evidence-Based Practice, 6th Edition offers unique insights into understanding, appraising, and applying published research to evidence-based practice. It is known for its authoritative content, time-tested systematic approach, and unique research example format newly redesigned for the sixth edition to better demonstrate how the steps of the research process relate to evidence-based nursing. "This would be excellent for student nurses, nurses new to research or any nurse with an interest in research." Reviewed by: Helen Reeves, St Giles Walsall Hospice on behalf of Nursing Times, December 2015 Authoritative content is written by two of the true pioneers in nursing research, who offer unique, first-hand insights into the field. Research examples provide practice in working with published studies, with many of the examples including Critical Appraisal and Implications for Practice sections. Clear, step-by-step organization introduces the research process and demonstrates how this systematic framework relates to evidence-based practice. Strong emphasis on evidence-based practice helps you develop skills in studying and appraising published research, so you are prepared for your role in working with research evidence. Critical Appraisal Guidelines boxes provide step-by-step guidance in appraising published research studies. Emphasis on critical appraisal versus critique reflects contemporary usage in nursing research and evidence-based practice. Balanced coverage of qualitative research prepares you to approach research questions and clinical questions with an unbiased view of the researcher's methodology. Presentation of two different appraisal processes covers both the traditional in-depth critical appraisal process that prepares you for graduate-level work in research, and the concise, practice-focused research appraisal process that equips you for quick and accurate evaluation of the applicability of research findings to clinical practice. NEW! Redesigned research example format includes research examples have been thoroughly redesigned with a clear hierarchy of subcategories. NEW! Improved focus on need-to-know content and greater use of bulleting, creative illustrations, and tables, employs a more consistent, streamlined approach from chapter to chapter. NEW! Updated research examples ensure you are learning through the most clinically relevant topics and studies. NEW! Detailed directions on how to critically appraise research syntheses — such as systematic reviews, meta-analyses, meta-syntheses, and mixed-methods systematic reviews — increase your understanding of the types of research syntheses conducted in nursing and how to determine the quality of these syntheses and the relevance of their findings for practice. NEW! A unique emphasis on QSEN, aided by the input of a QSEN consultant, increases the book’s relevance to national curriculum standards and promotes the safe practice of nursing by using the most current research. NEW! Chapter on the Enhanced Literature Review provides guidelines for structure of reviews written for different purposes. NEW! More practically focused chapter on Outcomes Research better addresses the trending topic of outcomes research. NEW! Expanded coverage of mixed-methods research and translational research responds to the growing emphasis on these research emphases. NEW! Expanded coverage of cultural competency and cultural validity

Designing and Conducting Research in Education

Author: Clifford J. Drew,Michael L. Hardman,John L. Hosp

Publisher: SAGE

ISBN: 1412960746

Category: Education

Page: 406

View: 8857

The research process in this book begins with identification of the research question and proceeds through each step including planning data collection, actual collection and analysis of the data, and writing the report. This text proceeds through multiple methodologies including experimental and non-experimental, quantitative and qualitative. At every step the emphasis is on planning and executing the study. Key features: o Simulations and feedback that may be used in class sessions for both individual and small group participation o Pedagogy to help students plan and conduct a research project in an actual classroom o Examples that demonstrate and explain what constitutes good and poor research questions o Case studies and ′real life′ examples related to education o A Student Web site that provides students with the opportunity to interact with contemporary articles. This book provides an introduction to research that emphasizes the fundamental concepts of planning and design. It is designed to be a core text for the very first course on research methods.

Introduction to Statistics and Data Analysis

Author: Roxy Peck,Chris Olsen,Jay L. Devore

Publisher: Cengage Learning

ISBN: 0840054904

Category: Mathematics

Page: 944

View: 530

Roxy Peck, Chris Olsen, and Jay Devore's new edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including the frequent substitution of words for symbols--helps students grasp concepts and cement their comprehension. Hands-on activities and interactive applets allow students to practice statistics firsthand. INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 4th Edition, includes updated coverage of the graphing calculator as well as expanded coverage of probability. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Understanding Nursing Research

Building an Evidence-Based Practice

Author: Nancy Burns,Susan K. Grove

Publisher: Elsevier Health Sciences

ISBN: 1437726550

Category: Medical

Page: 592

View: 881

Learn how to evaluate and apply research with the #1 nursing research book! Understanding Nursing Research: Building an Evidence-Based Practice is known for its authoritative content, a time-tested step-by-step approach, and abundant use of research examples. With improved clarity and readability, the new edition strengthens its focus on evidence-based practice to better demonstrate how the steps of the research process relate to evidence-based nursing. Written by two of the leaders in the field of nursing research, Nancy Burns and Susan K. Grove, this full-color text offers unique insights into understanding, appraising, and applying published research to evidence-based practice. Authoritative content is written by two of the true pioneers in nursing research, who offer unique, first-hand insights into the field. Research examples provide practice in working with published studies, with many of the examples including Critical Appraisal and Implications for Practice sections. A clear, step-by-step organization introduces the research process and demonstrates how this systematic framework relates to evidence-based practice. An expanded emphasis on evidence-based practice helps you develop skills in studying and appraising published research, so you are prepared for your role in working with research evidence. Enhanced coverage of qualitative research allows prepares you to approach research questions and clinical questions with an unbiased view of the researcher's methodology. Two different appraisal processes are included: A traditional in-depth critical appraisal process prepares you for graduate-level work in research. A concise, practice-focused research appraisal process equips you for quick and accurate evaluation of the applicability of research findings to clinical practice. Updated research examples prepare you for evidence-based practice by using the physiologic conditions and hospitalized patients seen in clinicals.

Data Analysis and Presentation Skills

An Introduction for the Life and Medical Sciences

Author: Jackie Willis

Publisher: John Wiley & Sons

ISBN: 0470011319

Category: Science

Page: 196

View: 360

Data Analysis and Presentation Skills: An Introduction for the Life and Medical Sciences is an invaluable text allowing students to develop appropriate key skills when designing experiments, generating results, analysing data and ultimately presenting findings to academics and referees. Taking a hands-on approach, each of these key areas is introduced clearly and carefully, showing how to access and evaluate information using a variety of resources. Basic analytical theory is gradually introduced alongside practical applications to enhance student understanding. The reader is shown how to present data in charts using Microsoft Excel and statistical analysis is carefully explained showing clearly how to manipulate data in spreadsheets and analyse the results using commonly used tests. A section is also included on the use of PowerPoint as well as giving advice on how to prepare a short talk or seminar. Includes numerous relevant examples and case studies drawn from the Life Sciences Guidance on how to complete and present practical and project work through to postgraduate dissertation. Clear step-by-step introduction to Microsoft Excel, presentation skills and statistical analysis. Invaluable for all students within the Life and Medical Sciences

Research and Evaluation in Education and Psychology

Integrating Diversity with Quantitative, Qualitative, and Mixed Methods

Author: Donna M. Mertens

Publisher: SAGE

ISBN: 9780761928058

Category: Education

Page: 507

View: 8550

The Second Edition continues and expands upon the approach that made the first edition an international bestseller. It includes sections and chapters on: the analysis of methodological advances in conducting research in culturally complex communities; coverage of electronic resources now available to researchers and evaluators; an additional emphasis on program evaluation; and, a new chapter on mixed methods research. Each chapter carefully explains a step of the research process from literature review to analysis and reporting. Additionally, sample studies and abstracts are included in each chapter to illustrate the concepts discussed in that section of the book.

Handbook of Statistical Analysis and Data Mining Applications

Author: Robert Nisbet,John Elder,Gary Miner

Publisher: Academic Press

ISBN: 9780080912035

Category: Mathematics

Page: 864

View: 7638

The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. Written "By Practitioners for Practitioners" Non-technical explanations build understanding without jargon and equations Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models Practical advice from successful real-world implementations Includes extensive case studies, examples, MS PowerPoint slides and datasets CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book

Statistik-Workshop für Programmierer

Author: Allen B. Downey

Publisher: O'Reilly Germany

ISBN: 3868993436

Category: Computers

Page: 160

View: 2311

Wenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.

Visualize This!

Author: Nathan Yau

Publisher: John Wiley & Sons

ISBN: 3527760229

Category: Statistics / Graphic methods / Data processing

Page: 422

View: 6922

A guide on how to visualise and tell stories with data, providing practical design tips complemented with step-by-step tutorials.

Statistics in Criminal Justice

Analysis and Interpretation

Author: Jeffery T. Walker

Publisher: Jones & Bartlett Learning

ISBN: 9780834210868

Category: Law

Page: 362

View: 9548

Criminal Justice / Law Enforcement

Statistics for Imaging, Optics, and Photonics

Author: Peter Bajorski

Publisher: John Wiley & Sons

ISBN: 1118121945

Category: Mathematics

Page: 408

View: 7727

A vivid, hands-on discussion of the statistical methods in imaging, optics, and photonics applications In the field of imaging science, there is a growing need for students and practitioners to be equipped with the necessary knowledge and tools to carry out quantitative analysis of data. Providing a self-contained approach that is not too heavily statistical in nature, Statistics for Imaging, Optics, and Photonics presents necessary analytical techniques in the context of real examples from various areas within the field, including remote sensing, color science, printing, and astronomy. Bridging the gap between imaging, optics, photonics, and statistical data analysis, the author uniquely concentrates on statistical inference, providing a wide range of relevant methods. Brief introductions to key probabilistic terms are provided at the beginning of the book in order to present the notation used, followed by discussions on multivariate techniques such as: Linear regression models, vector and matrix algebra, and random vectors and matrices Multivariate statistical inference, including inferences about both mean vectors and covariance matrices Principal components analysis Canonical correlation analysis Discrimination and classification analysis for two or more populations and spatial smoothing Cluster analysis, including similarity and dissimilarity measures and hierarchical and nonhierarchical clustering methods Intuitive and geometric understanding of concepts is emphasized, and all examples are relatively simple and include background explanations. Computational results and graphs are presented using the freely available R software, and can be replicated by using a variety of software packages. Throughout the book, problem sets and solutions contain partial numerical results, allowing readers to confirm the accuracy of their approach; and a related website features additional resources including the book's datasets and figures. Statistics for Imaging, Optics, and Photonics is an excellent book for courses on multivariate statistics for imaging science, optics, and photonics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for professionals working in imaging, optics, and photonics who carry out data analyses in their everyday work.

Adverse Impact Analysis

Understanding Data, Statistics, and Risk

Author: Scott B. Morris,Eric M. Dunleavy

Publisher: Psychology Press

ISBN: 1315301423

Category: Business & Economics

Page: 400

View: 8326

Compliance with federal equal employment opportunity regulations, including civil rights laws and affirmative action requirements, requires collection and analysis of data on disparities in employment outcomes, often referred to as adverse impact. While most human resources (HR) practitioners are familiar with basic adverse impact analysis, the courts and regulatory agencies are increasingly relying on more sophisticated methods to assess disparities. Employment data are often complicated, and can include a broad array of employment actions (e.g., selection, pay, promotion, termination), as well as data that span multiple protected groups, settings, and points in time. In the era of "big data," the HR analyst often has access to larger and more complex data sets relevant to employment disparities. Consequently, an informed HR practitioner needs a richer understanding of the issues and methods for conducting disparity analyses. This book brings together the diverse literature on disparity analysis, spanning work from statistics, industrial/organizational psychology, human resource management, labor economics, and law, to provide a comprehensive and integrated summary of current best practices in the field. Throughout, the description of methods is grounded in the legal context and current trends in employment litigation and the practices of federal regulatory agencies. The book provides guidance on all phases of disparity analysis, including: How to structure diverse and complex employment data for disparity analysis How to conduct both basic and advanced statistical analyses on employment outcomes related to employee selection, promotion, compensation, termination, and other employment outcomes How to interpret results in terms of both practical and statistical significance Common practical challenges and pitfalls in disparity analysis and strategies to deal with these issues