Methods in Behavioral Research

Methods in Behavioral Research

Methods in Behavioral Research

Methods in Behavioral Research by Paul Cozby and Scott Bates
Methods in Behavioral Research continues to guide students toward success by helping them study smarter and more efficiently. Cozby and Bates provide helpful pedagogy, rich examples, and a clear voice in their approach to methodological decision-making.
Ebook format: PDF
Ebook page: 446
File size: 8.31 MB

$40.00

Probability and Stochastic Processes

Probability and Stochastic Processes

Probability and Stochastic Processes

Probability and Stochastic Processes by Ionut Florescu
A comprehensive and accessible presentation of probability and stochastic processes with emphasis on key theoretical concepts and real-world applications With a sophisticated approach, Probability and Stochastic Processes successfully balances theory and applications in a pedagogical and accessible format. The book s primary focus is on key theoretical notions in probability to provide a foundation for understanding concepts and examples related to stochastic processes. Organized into two main sections, the book begins by developing probability theory with topical coverage on probability measure; random variables; integration theory; product spaces, conditional distribution, and conditional expectations; and limit theorems. The second part explores stochastic processes and related concepts including the Poisson process, renewal processes, Markov chains, semi-Markov processes, martingales, and Brownian motion. Featuring a logical combination of traditional and complex theories as well as practices, Probability and Stochastic Processes also includes: * Multiple examples from disciplines such as business, mathematical finance, and engineering * Chapter-by-chapter exercises and examples to allow readers to test their comprehension of the presented material * A rigorous treatment of all probability and stochastic processes concepts An appropriate textbook for probability and stochastic processes courses at the upper-undergraduate and graduate level in mathematics, business, and electrical engineering, Probability and Stochastic Processes is also an ideal reference for researchers and practitioners in the fields of mathematics, engineering, and finance.
Ebook format: PDF
Ebook page: 579
File size: 3.63 MB

$20.00

Introductory Statistics for the Health Sciences

Introductory Statistics for the Health Sciences

Introductory Statistics for the Health Sciences

Introductory Statistics for the Health Sciences by Lise DeShea and Larry E. Toothaker
Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets from published research. Examples come from many areas of the health sciences, including medicine, nursing, pharmacy, dentistry, and physical therapy, but are understandable to students in any field. The book can be used in a first-semester course in a health sciences program or in a service course for undergraduate students who plan to enter a health sciences program.
The book begins by explaining the research context for statistics in the health sciences, which provides students with a framework for understanding why they need statistics as well as a foundation for the remainder of the text. It emphasizes kinds of variables and their relationships throughout, giving a substantive context for descriptive statistics, graphs, probability, inferential statistics, and interval estimation. The final chapter organizes the statistical procedures in a decision tree and leads students through a process of assessing research scenarios.
Ebook format: PDF
Ebook page: 578
File size: 7.21 MB

$20.00

Handbook of Spatial Point-Pattern Analysis in Ecology

Handbook of Spatial Point-Pattern Analysis in Ecology

Handbook of Spatial Point-Pattern Analysis in Ecology

Handbook of Spatial Point-Pattern Analysis in Ecology (Chapman & Hall/CRC Applied Environmental Statistics) by Thorsten Wiegand and Kirk A. Moloney
Although numerous statistical methods for analyzing spatial point patterns have been available for several decades, they haven’t been extensively applied in an ecological context. Addressing this gap, Handbook of Spatial Point-Pattern Analysis in Ecology shows how the techniques of point-pattern analysis are useful for tackling ecological problems. Within an ecological framework, the book guides readers through a variety of methods for different data types and aids in the interpretation of the results obtained by point-pattern analysis.
Ideal for empirical ecologists who want to avoid advanced theoretical literature, the book covers statistical techniques for analyzing and interpreting the information contained in ecological patterns. It presents methods used to extract information hidden in spatial point-pattern data that may point to the underlying processes. The authors focus on point processes and null models that have proven their immediate utility for broad ecological applications, such as cluster processes.
Along with the techniques, the handbook provides a comprehensive selection of real-world examples. Most of the examples are analyzed using Programita, a continuously updated software package based on the authors’ many years of teaching and collaborative research in ecological point-pattern analysis. Programita is tailored to meet the needs of real-world applications in ecology. The software and a manual are available online.
Ebook format: PDF
Ebook page: 538
File size: 12.20 MB

$15.00

Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis

Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis

Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis

Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) by Leslie Rutkowski and Matthias von Davier

Technological and statistical advances, along with a strong interest in gathering more information about the state of our educational systems, have made it possible to assess more students, in more countries, more often, and in more subject domains. The Handbook of International Large-Scale Assessment: Background, Technical Issues, and Methods of Data Analysis brings together recognized scholars in the field of ILSA, behavioral statistics, and policy to develop a detailed guide that goes beyond database user manuals.
After highlighting the importance of ILSA data to policy and research, the book reviews methodological aspects and features of the studies based on operational considerations, analytics, and reporting. The book then describes methods of interest to advanced graduate students, researchers, and policy analysts who have a good grounding in quantitative methods, but who are not necessarily quantitative methodologists. In addition, it provides a detailed exposition of the technical details behind these assessments, including the test design, the sampling framework, and estimation methods, with a focus on how these issues impact analysis choices.

Ebook format: PDF
Ebook page: 623
File size: 8.21 MB

$15.00

Essentials of Statistics (5th Edition)

Essentials of Statistics (5th Edition)

Essentials of Statistics (5th Edition)

Essentials of Statistics (5th Edition) by Mario F. Triola
Essentials of Statistics raises the bar with every edition by incorporating an unprecedented amount of real and interesting data that will help instructors connect with students today, and help them connect statistics to their daily lives. The Fifth Edition contains more than 1,800 exercises, 89% of which use real data and 85% of which are new. Hundreds of examples are included, 91% of which use real data and 84% of which are new. New coverage of Ethics in Statistics highlights new guidelines that have been established in the industry.
Ebook format: PDF
Ebook page: 701
File size: 19.47 MB

$40.00

Statistical Methods for Microarray Data Analysis: Methods and Protocols

Statistical Methods for Microarray Data Analysis: Methods and Protocols

Statistical Methods for Microarray Data Analysis: Methods and Protocols

Statistical Methods for Microarray Data Analysis: Methods and Protocols (Methods in Molecular Biology) by Andrei Y. Yakovlev and Lev Klebanov
Microarrays for simultaneous measurement of redundancy  of RNA species are used in fundamental biology as well as in medical research. Statistically,a microarray may be considered as an observation of very high dimensionality equal to the number of expression levels measured on it. In Statistical Methods for Microarray Data Analysis: Methods and Protocols, expert researchers in the field detail many methods and techniques used to study microarrays, guiding the reader from microarray technology to statistical problems of specific multivariate data analysis. Written in the highly successful Methods in Molecular Biology™ series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory.
Ebook format: PDF
Ebook page: 225
File size: 3.21 MB

$37.00

A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics by David P. Landau and Kurt Binder
Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This fourth edition contains extensive new material describing numerous powerful algorithms not covered in previous editions, in some cases representing new developments that have only recently appeared. Older methodologies whose impact was previously unclear or unappreciated are also introduced, in addition to many small revisions that bring the text and cited literature up to date. This edition also introduces the use of petascale computing facilities in the Monte Carlo arena. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.
Ebook format: PDF
Ebook page: 537
File size: 12.58 MB

$25.00

Statistical Thinking for Non-Statisticians in Drug Regulation

Statistical Thinking for Non-Statisticians in Drug Regulation

Statistical Thinking for Non-Statisticians in Drug Regulation

Statistical Thinking for Non-Statisticians in Drug Regulation by Richard Kay
Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials.
It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials.
Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis.
Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.
Ebook format: PDF
Ebook page: 370
File size: 2.12 MB

$25.00

Using Multivariate Statistics (6th Edition)

Using Multivariate Statistics (6th Edition)

Using Multivariate Statistics (6th Edition)

Using Multivariate Statistics (6th Edition) by Barbara G. Tabachnick and Linda S. Fidell

Using Multivariate Statistics, 6^th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. This text’s practical approach focuses on the benefits and limitations of applications of a technique to a data set — when, why, and how to do it.

Learning Goals

Upon completing this book, readers should be able to:

• Learn to conduct numerous types of multivariate statistical analyses
• Find the best technique to use
• Understand Limitations to applications
• Learn how to use SPSS and SAS syntax and output

Ebook format: PDF
Ebook page: 1018
File size: 5.89 MB

$65.00

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015 (Springer Proceedings in Mathematics & Statistics) by Ansgar Steland and Ewaryst Rafajlowicz

This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering.
Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few.
This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.

Ebook format: PDF
Ebook page: 478
File size: 5.32 MB

$40.00

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis by Wolfgang Karl Härdle and Léopold Simar
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis.
The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features:
A new chapter on Variable Selection (Lasso, SCAD and Elastic Net)
All exercises are supplemented by R and MATLAB code that can be found on www.quantlet.de.
The practical exercises include solutions that can be found in Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.
Ebook format: PDF
Ebook page: 581
File size: 11.30 MB

$30.00

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators (Wiley Series in Probability and Statistics) by Tailen Hsing and Randall Eubank
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA). The self contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self adjoint and non self adjoint operators. The probabilistic foundation for FDA is described from the perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principle components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis. This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.
Ebook format: PDF
Ebook page: 364
File size: 2.34 MB

$50.00

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015 (Springer Proceedings in Mathematics & Statistics) by Ansgar Steland and Ewaryst Rafajlowicz

This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering.
Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few.

Ebook format: PDF
Ebook page: 478
File size: 5.32 MB

$55.00

Foundations of Linear and Generalized Linear Models

Foundations of Linear and Generalized Linear Models

Foundations of Linear and Generalized Linear Models

Foundations of Linear and Generalized Linear Models (Wiley Series in Probability and Statistics) by Alan Agresti
A valuable overview of the most important ideas and results in statistical modeling
Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding.
The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: * An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods * An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems * Numerous examples that use R software for all text data analyses * More than 400 exercises for readers to practice and extend the theory, methods, and data analysis * A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.

Ebook format: PDF
Ebook page: 527
File size: 4.74 MB

$50.00

The Routledge Handbook of Planning Research Methods

The Routledge Handbook of Planning Research Methods

The Routledge Handbook of Planning Research Methods

The Routledge Handbook of Planning Research Methods (Routledge Handbooks) by Elisabete A. Silva and Patsy Healey

The Routledge Handbook of Planning Research Methods is an expansive look at the traditions, methods, and challenges of research design and research projects in contemporary urban planning. Through case studies, an international group of researchers, planning practitioners, and planning academics and educators, all recognized authorities in the field, provide accounts of designing and implementing research projects from different approaches and venues. This book shows how to apply quantitative and qualitative methods to projects, and how to take your research from the classroom to the real world. The book is structured into sections focusing on
Beginning planning research
Research design and development
Rediscovering qualitative methods
New advances in quantitative methods
Turning research into action
With chapters written by leading scholars in spatial planning, The Routledge Handbook of Planning Research Methods is the most authoritative and comprehensive handbook on the topic, providing both established and ground breaking coverage of spatial planning research methods. The book is an invaluable resource for undergraduate and graduate level students, young professionals and practitioners in urban, regional, and spatial planning.

Ebook format: PDF
Ebook page: 572
File size: 6.76 MB

$85.00

Statistics for Management and Economics, Abbreviated

Statistics for Management and Economics, Abbreviated

Statistics for Management and Economics, Abbreviated

Statistics for Management and Economics, Abbreviated by Gerald Keller
Emphasizing applications over calculation, worldwide-bestseller STATISTICS FOR MANAGEMENT AND ECONOMICS, ABBREVIATED 10e vividly illustrates how vital statistical methods and tools are for today's managers?and teaches you how to apply them to business problems. Using a proven three-step "ICI" approach to problem solving, the text demonstrates how to IDENTIFY the correct statistical technique by focusing on the problem objective and data type; how to COMPUTE the statistics by hand, using Excel 2013, or using MINITAB 16; and how to INTERPRET results in the context of the problem. Incorporating various functional areas of business, data-driven examples, exercises, and cases give you hands-on practice applying statistical applications used by marketing managers, financial analysts, accountants, economists, and others. Completely current, the ABBREVIATED 10e also includes updated figure and data tables, MindTap™ Reader, and access to Data Analysis Plus via the textbook companion website.
Ebook format: PDF
Ebook page: 998
File size: 22.49 MB

$85.00

Encyclopedia of Survey Research Methods

Encyclopedia of Survey Research Methods

Encyclopedia of Survey Research Methods

Encyclopedia of Survey Research Methods by Paul J. Lavrakas
In conjunction with top survey researchers around the world and with Nielsen Media Research serving as the corporate sponsor, the Encyclopedia of Survey Research Methods presents state-of-the-art information and methodological examples from the field of survey research. Although there are other "how-to" guides and references texts on survey research, none is as comprehensive as this Encyclopedia, and none presents the material in such a focused and approachable manner. With more than 600 entries, this resource uses a Total Survey Error perspective that considers all aspects of possible survey error from a cost-benefit standpoint.
Ebook format: PDF
Ebook page: 1041
File size: 14.47 MB

$150.00

Handbook of Statistical Bioinformatics

Handbook of Statistical Bioinformatics

Handbook of Statistical Bioinformatics

Handbook of Statistical Bioinformatics (Springer Handbooks of Computational Statistics) by Henry Horng-Shing Lu and Bernhard Schölkopf
Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Ebook format: PDF
Ebook page: 623
File size: 8.67 MB

$100.00

Handbook of Computational Finance

Handbook of Computational Finance

Handbook of Computational Finance

Handbook of Computational Finance (Springer Handbooks of Computational Statistics) by Jin-Chuan Duan and Wolfgang Karl Härdle
Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.
Ebook format: PDF
Ebook page: 817
File size: 10.57 MB

$90.00