Data Analysis Using Stata

Using Stata for Statistical Analysis, Third Edition is a supplemental book for undergraduate and graduate level courses in research methods and statistical analysis where Stata is used. It can be appl

Providing information from data preparation and mean, median and mode, to regression, Lisa Daniels and Nicholas Minot use concise descriptions to help students understand the concepts behind statistic

"This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of usin

Introduces the latest developments in forecasting in advanced quantitative data analysisThis book presents advanced univariate multiple regressions, which can directly be used to forecast their depend

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be fou

The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data sci

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Py

Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approac

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how t

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how t

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary c

Qualitative and Mixed Methods Data Analysis Using Dedoose®: A Practical Approach for Research Across the Social Sciences provides both new and experienced researchers with a guided introduction to dea

Engaging and accessible, this book offers students a complete guide to using NVivo for qualitative data analysis. Drawing on their wealth of expertise, the authors offer detailed, practical advice tha

Engaging and accessible, this book offers students a complete guide to using NVivo for qualitative data analysis. Drawing on their wealth of expertise, the authors offer detailed, practical advice tha

Peck, Short, and Olsen's INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 6th Edition stresses interpretation and communication of statistical information through hands-on, activity based learning using

Almost 50 years have passed since the famous papers of Hugo Rietveld from the late sixties where he describes a method for the refinement of crystal structures from neutron powder diffraction data. So

This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent cas

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, a

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapt

This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data anal

Use Microsoft Azure to optimally design your data solutions and save time and money. Scenarios are presented covering analysis, design, integration, monitoring, and derivatives.This book is about data

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big

The book presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide variety of graphical d

Inspire students to pursue their own adventures in social research with this practical, hands-on introduction to data conceptualization, measurement, and association through active learning. Adventure

Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Da

A comprehensive source of generalized design data for most widely used fin surfaces in CHEs Compact Heat Exchanger Analysis, Design and Optimization: FEM and CFD Approach brings new concepts of design

"This book explores the extraction and prediction of patterns at multiple levels of abstraction. It involves a procedure handling both numeric and nominal data at once using a single method and the me

A Stata Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of Stata using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using Stata. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of Stata step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in Stata to produce original statistical analyses for evaluating causal claims. End-of-chapter

With an emphasis on experimental design and sampling, The Analysis of Ecological Data Using R presents all of the necessary statistical methods along with the ecological background for each problem. E

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are

This practical book is designed for applied researchers who want to use mixed models with their data. It discusses the basic principles of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables, and categorical and survival outcome variables. Emphasizing interpretation of results, the book develops the most important applications of mixed models, such as the study of group differences, longitudinal data analysis, multivariate mixed model analysis, IPD meta-analysis, and mixed model predictions. All examples are analyzed with STATA, and an extensive overview and comparison of alternative software packages is provided. All datasets used in the book are available for download, so readers can re-analyze the examples to gain a strong understanding of the methods. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other

This practical book is designed for applied researchers who want to use mixed models with their data. It discusses the basic principles of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables, and categorical and survival outcome variables. Emphasizing interpretation of results, the book develops the most important applications of mixed models, such as the study of group differences, longitudinal data analysis, multivariate mixed model analysis, IPD meta-analysis, and mixed model predictions. All examples are analyzed with STATA, and an extensive overview and comparison of alternative software packages is provided. All datasets used in the book are available for download, so readers can re-analyze the examples to gain a strong understanding of the methods. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other