Statistics and Mathematics

Uses statistics to teach SPSS, by interacting with the software and learning by inquiry and discovery. Twenty-three short chapters show how to use SPSS to compute the most common statistical tests.

This dynamic, student-focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool.

Written by Eva Lawrence and Kathrynn Adams, this study guide provides instructions for performing statistical calculations in IBM(R) SPSS (R) along with additional exercises to reinforce concepts in the text. It follows the main text, chapter by chapter, for easy assigning and studying.

Perfect as a brief core or supplementary text for undergraduate courses in statistics and research methods, Statistics for the Terrified is also an ideal refresher for students who have already taken a statistics course. Its informal and highly engaging narrative includes self-help strategies, numerous concrete examples, and a great deal of humor.

A long-standing, best-selling, comprehensive textbook covering all the mathematics required on upper level engineering mathematics undergraduate courses.

Business Statistics using Excel offers a step-by-step guide to the theory and methodology behind the use of statistics in business. Integrated screenshots offer clear guidance through each Excel process and exercises are imbedded throughout each chapter to ensure that students engage with the content and frequently test their understanding.

Presented through exciting examples, with an emphasis on understanding rather than computation, the Second Edition provides a crystal clear introduction to the main statistical procedures used in the psychological and social sciences.

Like its wildly popular predecessors 'Cabinet of Mathematical Curiosities' and 'Hoard of Mathematical Treasures', this book is a miscellany of over 150 mathematical curios and conundrums, packed with trademark humour and numerous illustrations.

Many students find the quantum intellectual leap between school and university maths to be too great, and some drop out as a result. This book has been written to counter this, by helping students cross the divide.

Inspiration and guidance for aspiring mathematicians

SAGE Dictionary of Statistics

In the bestselling tradition of Supercrunchers and Freakonomics a popular statistician and blogger provides a fascinating and entertaining narrative that dramatizes the hidden power of numbers and numerical relationships in everyday life.

The ideal review for the thousands of college students who enroll in intermediate algebra courses.

Takes in various branches of pure and applied mathematics, from algebra to mechanics and from number theory to statistics. Suitable for students at various levels, this book is also useful for economists, business people, engineers, technicians and scientists who use mathematics in the course of their work.

This book aims to explain, in clear non-technical language,what it is that mathematicians do, and how that differs from and builds on the mathematics that most people are familiar with from school. It is the ideal introduction for anyone who wishes to deepen their understanding of mathematics.

Part of a set of volumes that trace the development of mathematical ideas and the careers of the mathematicians responsible for them, this text covers the revival of projective geometry, the emergence of abstract algebra, the beginnings of topology, and the influence of Godel on recent study.

This wide-ranging dictionary covers over 2,300 statistical terms in accessible, jargon-free language. All existing entries and web links have been revised and updated to ensure that the content is as relevant as possible. An indispensable reference work for any students or professionals who come into contact with statistics at work or university.

With an emphasis on describing concepts, showing through example and illustrating points with graphs and displays, this book provides readers with a step-by-step introduction to using statistics.

Based on Neil J. Salkind's bestselling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative and personable.

Designed to heighten awareness of statistical ideas, this comprehensive and research-based text explores four main themes: describing, comparing, inter-relating, and uncertainty.

Written in an informal style, this book guides the reader gently through the field from the simplest descriptive statistics to multidimensional approaches. It's written in an accessible way, with few calculations and fewer equations, for readers from a broad set of academic disciplines ranging from archaeology to zoology.

From the author of 'The Music of the Primes' and 'Finding Moonshine' comes a short, lively book on five mathematical problems that just refuse be solved - and on how many everyday problems can be solved by maths.

This work guides the reader through the process of data analysis and features hints and warnings. It should be of interest to those studying quantitative methods in all disciplines, in particular marketing, management, economics and psychology.

Once again, bestselling author and award-winning teacher Andy Field hasn't just broken the traditional textbook mould with his new novel/textbook, he has forged the only statistics book on the market with a terrifying probability bridge, zombies and a talking cat!

Delivered in Evergreen's humorous and approachable style, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate the story in their data.

In this Very Short Introduction, Jacqueline Stedall explores the rich historical and cultural diversity of mathematical endeavour from the distant past to the present day, using illustrative case studies drawn from a range of times and places; including early imperial China, the medieval Islamic world, and nineteenth-century Britain.

Rev. ed. of: Computer-aided multivariate analysis. 4th ed. c2004.

The updated edition of this classic text introduces a range of techniques for exploring quantitative data. Beginning with an emphasis on descriptive statistics and graphical approaches, it moves on in later chapters to simple strategies for examining the associations between variables using inferential statistics such as chi squared.

100 of the most important mathematical concepts and their discoveries.

Twenty-three mathematical masterpieces for exploration and enlightenment

A thrilling account of an utterly brilliant and utterly eccentric Russian mathematician which sheds a rare light on the unique burden of genius

Encourages development of application and decision making skills for use in managing raw data and real-world projects. This book includes such topics as scattergrams and time series graphs, simple and multiple regressions, time series analysis, and random sampling.

The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.

A concise 'need-to-know' introduction to the essentials of statistics for business and management students with real-world examples and step-by-step tutorials for both Excel and SPSS to enhance and consolidate learning.

Written with those with limited mathematical and statistical knowledge in mind, this concise and practical guide helps researchers to do their research in new and alternative ways.

Provides advanced students with a comprehensive introduction to commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher level mathematics. Each technique chapter: discusses tests for assumptions of analysis, presents a small example and describes varieties of analysis.

Statistics is arguably the main means through which maths appears in non-maths courses. De-mystifying the basics for even the most maths-terrified of students, this book will inspire confident and accurate use of statistics for non-maths courses.

This easy-to-use guide identifies and addresses the areas where most students need help with basic mathematical problems that occur in everyday life and academic study and provides straightforward, practical tips and solutions that will enable you to assess and then improve your performance.

The ideal review for the thousands of college students who enroll in college mathematics courses.

For the 1 or 2 semester course in Business Statistics. Emphasizing the use of statistical software like Excel and Minitab, this comprehensive text offers a rich array of business examples, real data, and a unique step-by-step framework that allows students to learn by doing.

Thinking Mathematically unfolds the processes which lie at the heart of mathematics. It demonstrates how to encourage, develop, and foster the processes which seem to come naturally to mathematicians.

"Preface This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics. Although introductory in its early sections, the book is definitely not elementary in the sense of a first text in statistics. The mathematics used in our book is basic probability and statistics, elementary calculus, and linear algebra. A review of probability notation is given in Chapter 1 along with a more detailed list of topics assumed to have been studied. The practical orientation of the book means that the reader's previous experience in probability, statistics, and linear algebra should ideally have included strong computational components. To write an introductory text alone would leave many readers with only a taste of the conceptual elements but no guidance for venturing into genuine practical applications, beyond those where Bayesian methods agree essentially with standard non-Bayesian analyses. On the other hand, we feel it would be a mistake to present the advanced methods without first introducing the basic concepts from our data-analytic perspective. Furthermore, due to the nature of applied statistics, a text on current Bayesian methodology would be incomplete without a variety of worked examples drawn from real applications. To avoid cluttering the main narrative, there are bibliographic notes at the end of each chapter and references at the end of the book"--

Bayesian Essentials with R

A Practical Approach to using Multivariate Analyses Using Multivariate Statistics, 6th 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.