In this important new text, Paul Sullivan introduces readers to a qualitative methodology rooted in the analysis of dialogue and subjectivity: the dialogical approach. Sullivan unpacks the theory behi
First published as What is Quantitative Longitudinal Data Analysis?, this title is now available as part of the Bloomsbury Research Methods series.Across the social sciences, there is widespread agree
Longitudinal data analysis for biomedical and behavioral sciences This innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in t
Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport per
This modern introduction to seismic data processing in both exploration and global geophysics demonstrates practical applications through real data and tutorial examples. The underlying physics and mathematics of the various seismic analysis methods are presented, giving students an appreciation of their limitations and potential for creating models of the sub-surface. Designed for a one-semester course, this textbook discusses key techniques within the context of the world's ever increasing need for petroleum and mineral resources - equipping upper undergraduate and graduate students with the tools they need for a career in industry. Examples presented throughout the text allow students to compare different methods and can be demonstrated using the instructor's software of choice. Exercises at the end of sections enable students to check their understanding and put the theory into practice and are complemented by solutions for instructors and additional case study examples online to c
This is the second edition of a very popular applied reference/textbook on the analysis of data from surveys. It is one of the most well-regarded books in the field, and is widely used for research an
Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; found
A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts.
Just Plain Data Analysis is designed to teach students statistical literacy skills that they can use to evaluate and construct arguments about public affairs issues grounded in numerical evidence. Wit
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
From a preeminent authority—a modern and applied treatment of multiway data analysis This groundbreaking book is the first of its kind to present methods for analyzing multiway data by applying multi
Atmospheric analysis is the method of transforming the enormous and scattered database of atmospheric observations into the powerful mathematical and physical tools required to meet the growing demand for atmospheric data. Atmospheric Data Analysis is intended to fill a void in the atmospheric science literature and curricula. The book is self contained, and includes topics important in several other fields outside atmospheric observation, including atmospheric dynamics and statistics. It outlines the physical and mathematical basis of all aspects of atmospheric analysis. The emphasis is on the theoretical foundation of the subject and most of the development is analytic, but many practical considerations and examples are introduced. There are numerous exercises at the end of each chapter to aid the student in comprehending the material.
The eighth edition of Multivariate Data Analysis provides an updated perspective on the analysis of all types of data as well as introducing some new perspectives and techniques that are foundational
