Introduction to Bayesian Statistics

This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes mul

Do you use language corpora in your research or study, but find that you struggle with statistics? This practical introduction will equip you to understand the key principles of statistical thinking and apply these concepts to your own research, without the need for prior statistical knowledge. The book gives step-by-step guidance through the process of statistical analysis and provides multiple examples of how statistical techniques can be used to analyse and visualise linguistic data. It also includes a useful selection of discussion questions and exercises which you can use to check your understanding. The book comes with a Companion website, which provides additional materials (answers to exercises, datasets, advanced materials, teaching slides etc.) and Lancaster Stats Tools online (http://corpora.lancs.ac.uk/stats), a free click-and-analyse statistical tool for easy calculation of the statistical measures discussed in the book.

Do you use language corpora in your research or study, but find that you struggle with statistics? This practical introduction will equip you to understand the key principles of statistical thinking and apply these concepts to your own research, without the need for prior statistical knowledge. The book gives step-by-step guidance through the process of statistical analysis and provides multiple examples of how statistical techniques can be used to analyse and visualise linguistic data. It also includes a useful selection of discussion questions and exercises which you can use to check your understanding. The book comes with a Companion website, which provides additional materials (answers to exercises, datasets, advanced materials, teaching slides etc.) and Lancaster Stats Tools online (http://corpora.lancs.ac.uk/stats), a free click-and-analyse statistical tool for easy calculation of the statistical measures discussed in the book.

This fourth Edition presents new examples on submodules, derived type i/o, object oriented programming, abstract interfaces and procedure pointers, C interop, sorting and searching, statistics and con

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

Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences by William E. Wagner, III and Brian J. Gillespie is designed to be paired with any undergraduate introduction to resear

This text grew out of the author’s notes for a course that he has taught for many years to a diverse group of undergraduates. The early introduction to the major concepts engages students immedi

John E. Freund's Mathematical Statistics with Applications , Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage tha

A comprehensive account of both basic and advanced material in phylogeny estimation, focusing on computational and statistical issues. No background in biology or computer science is assumed, and there is minimal use of mathematical formulas, meaning that students from many disciplines, including biology, computer science, statistics, and applied mathematics, will find the text accessible. The mathematical and statistical foundations of phylogeny estimation are presented rigorously, following which more advanced material is covered. This includes substantial chapters on multi-locus phylogeny estimation, supertree methods, multiple sequence alignment techniques, and designing methods for large-scale phylogeny estimation. The author provides key analytical techniques to prove theoretical properties about methods, as well as addressing performance in practice for methods for estimating trees. Research problems requiring novel computational methods are also presented, so that graduate stud

Jesus turned water into wine, Mohammad split the moon into two, and Buddha walked and spoke immediately upon birth. According to recent statistics, even in the present age of advanced science and tech

Probability has applications in many areas of modern science, not to mention in our daily life. Its importance as a mathematical discipline cannot be overrated, and it is a fascinating and surprising topic in its own right. This engaging textbook with its easy-to-follow writing style provides a comprehensive yet concise introduction to the subject. It covers all of the standard material for undergraduate and first-year-graduate-level courses as well as many topics that are usually not found in standard texts, such as Bayesian inference, Markov chain Monte Carlo simulation, and Chernoff bounds.

This book provides a clear, precise, and structured introduction to stochastics and probability theory. It includes many descriptive examples, such as games of chance, which help promote understanding

This accessible, practice-oriented and compact text provides a hands-on introduction to market research. Using the market research process as a framework, it explains how to collect and describe data

This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, th

Reproducing kernel Hilbert spaces have developed into an important tool in many areas, especially statistics and machine learning, and they play a valuable role in complex analysis, probability, group representation theory, and the theory of integral operators. This unique text offers a unified overview of the topic, providing detailed examples of applications, as well as covering the fundamental underlying theory, including chapters on interpolation and approximation, Cholesky and Schur operations on kernels, and vector-valued spaces. Self-contained and accessibly written, with exercises at the end of each chapter, this unrivalled treatment of the topic serves as an ideal introduction for graduate students across mathematics, computer science, and engineering, as well as a useful reference for researchers working in functional analysis or its applications.

This book aids health research students in understanding statistics, both practically and methodogically. The author's approach views statistics as a language of logic rather than mathematics wi

An insight into statistics is a comprehensive introduction to probability theory and statistical methods in the social sciences. The book forms the basis for empirical studies within disciplines such

This book serves as an introduction to the statistics programme Stata. The primary audience is students and others using statistical software for the first time. Experienced users of other statistical

The subject of data fitting bridges many disciplines, especially those traditionally dealing with statistics like physics, mathematics, engineering, biology, economy, or psychology, but also more rece

Providing a practical, hands-on introduction to data conceptualization, measurement and association, this book gives students step-by-step instruction on data analysis using the latest version of SPSS

Why are poor countries poor and rich countries rich? How are wealth and poverty related to changes in health, life expectancy, education, population growth and politics? This non-technical introduction to development studies explores the dynamics of socio-economic development and stagnation in developing countries. Thoroughly updated and revised, this second edition includes new material on the effects of the 2008 financial crisis, the emergence of the BRICS economies, the role of institutions in development and the accelerated growth of economies in Africa and Asia. Taking a comparative approach, Szirmai places contemporary debates within their broader contexts and combines insights and theories from economics, economic history, political science, anthropology and sociology. Each chapter includes comparative statistics and time series for thirty-one developing countries. Assuming no prior knowledge of economics, this book is well-suited for students in interdisciplinary development st

Why are poor countries poor and rich countries rich? How are wealth and poverty related to changes in health, life expectancy, education, population growth and politics? This non-technical introduction to development studies explores the dynamics of socio-economic development and stagnation in developing countries. Thoroughly updated and revised, this second edition includes new material on the effects of the 2008 financial crisis, the emergence of the BRICS economies, the role of institutions in development and the accelerated growth of economies in Africa and Asia. Taking a comparative approach, Szirmai places contemporary debates within their broader contexts and combines insights and theories from economics, economic history, political science, anthropology and sociology. Each chapter includes comparative statistics and time series for thirty-one developing countries. Assuming no prior knowledge of economics, this book is well-suited for students in interdisciplinary development st

This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes

The Survivor's Guide to R provides a gentle, but thorough, introduction to R. It is an ideal supplement to any introductory statistics text or a practical field guide for those who want to use the po

This book is intended as a text for a two-quarter or two-semester post-calculus introduction to probability and mathematical statistics for undergraduate students in their junior or senior year, and a

Taking a biological perspective, this text provides an introduction to foundational topics in science, probability, and mathematical statistics for advanced undergraduate and graduate students in biol

Converting Data into Evidence: A Statistics Primer for the Medical Practitioner provides a thorough introduction to the key statistical techniques that medical practitioners encounter throughout their

Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the stat

This volume provides a modern introduction to stochastic geometry, random fields and spatial statistics at a (post)graduate level. It is focused on asymptotic methods in geometric probability includi

Across the last forty years, epidemiology has developed into a vibrant scientific discipline that brings together the social and biological sciences, incorporating everything from statistics to the ph

Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis

Used by hundreds of thousands of students, INTRODUCTION TO PROBABILITY AND STATISTICS, Fourteenth Edition, blends proven coverage with new innovations to ensure you gain a solid understanding of stati

Snijders (statistics in the social sciences, U. of Oxford) and Bosker (U. of Groningen, The Netherlands) offer a textbook for absolute beginners in multilevel analysis, which analyzes data with comple

Richard Stanley's two-volume basic introduction to enumerative combinatorics has become the standard guide to the topic for students and experts alike. This thoroughly revised second edition of Volume 1 includes ten new sections and more than 300 new exercises, most with solutions, reflecting numerous new developments since the publication of the first edition in 1986. The author brings the coverage up to date and includes a wide variety of additional applications and examples, as well as updated and expanded chapter bibliographies. Many of the less difficult new exercises have no solutions so that they can more easily be assigned to students. The material on P-partitions has been rearranged and generalized; the treatment of permutation statistics has been greatly enlarged; and there are also new sections on q-analogues of permutations, hyperplane arrangements, the cd-index, promotion and evacuation and differential posets.

Rather than bombarding students with lots of statistics, You May Ask Yourself emphasizes the "big ideas" of the discipline and encourages students to ask meaningful questions. Faculty love Conley's "

This comprehensive introduction to probability and statistics will give you the solid grounding you need no matter what your engineering specialty. Through the use of lively and realistic examples, t

Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to sele