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Search the UJLink: Library Catalogue for Mathematics and Statistics books on Level 4 @ the APK Library.
Computer Age Statistical Inference: algorithms, evidence, and data science (Print + Online, Cambridge) by
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
100 Questions (and Answers) about Statistics by
This short book is ideal for those individuals who need a refresher as to what the important topics are within statistics as well as for those who are entirely new to the discipline and need a resource as to what the key questions are that one might ask.
An Introduction to Statistics: an active learning approach by
The authors encourage an active approach to learning statistics through many in-depth activities that give students the opportunity to test or demonstrate their understanding of statistical concepts. The Second Edition is based on contemporary research on memory and the "testing effect" which requires students to answer questions to facilitate their long-term retention.
Statistics for People Who (Think They) Hate Statistics (International Student Edition) by
The Sixth Edition of Neil J. Salkind's best-selling Statistics for People Who (Think They) Hate Statistics promises to ease student anxiety around an often intimidating subject with a humorous, personable, and informative approach. Salkind guides students through various statistical procedures, beginning with descriptive statistics, correlation, and graphical representation of data, and ending with inferential techniques and analysis of variance.AncillariesStudent resources A complete online action plan allows you to track your progress and enhance your learning experience Learning objectives reinforce the most important material Mobile-friendly practice quizzes allow for independent assessment by students of their mastery of course material Mobile-friendly eFlashcards strengthen understanding of key terms and concepts Multimedia content includes original SAGE videos that appeal to students with different learning styles EXCLUSIVE! Access to full-text SAGE journal articles that have been carefully selected to support and expand on the concepts presented in each chapter Data sets accompany exercises and problems in the book. Lecturer resources Test banks provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert personalized questions to effectively assess students' progress and understanding Editable, chapter-specific PowerPoint#65533; slides offer complete flexibility for creating a multimedia presentation for the course Lecture notes summarize key concepts by chapter to ease preparation for lectures and class discussions Sample course syllabi for semester and quarter courses provide suggested models for structuring one's course Data sets accompany exercises and problems in the book. Chapter-specific discussion questions help launch classroom interaction by prompting students to engage with the material and by reinforcing important content. Lively and stimulating ideas for class activities that can be used in class to reinforce active learning. The activities apply to individual or group projects. Multimedia content includes original SAGE videos that appeal to students with different learning styles EXCLUSIVE! Access to full-text SAGE journal articles have been carefully selected to support and expand on the concepts presented in each chapter to encourage students to think critically A Course cartridge provides easy LMS integration ?
Statistics for Big Data for Dummies by
The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word "statistics" alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining'without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.
Using R with Multivariate Statistics by
This book helps students and researchers in the social and behavioural sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.
Probability and Statistics with R, Second Edition by
Cohesively Incorporates Statistical Theory with R Implementation Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an intermediate undergraduate course, Probability and Statistics with R, Second Editionexplores how some of these new packages make analysis easier and more intuitive as well as create more visually pleasing graphs. New to the Second Edition Improvements to existing examples, problems, concepts, data, and functions New examples and exercises that use the most modern functions Coverage probability of a confidence interval and model validation Highlighted R code for calculations and graph creation Gets Students Up to Date on Practical Statistical Topics Keeping pace with today's statistical landscape, this textbook expands your students' knowledge of the practice of statistics. It effectively links statistical concepts with R procedures, empowering students to solve a vast array of real statistical problems with R. Web Resources A supplementary website offers solutions to odd exercises and templates for homework assignments while the data sets and R functions are available on CRAN.
Learning Statistics Using R by
Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Lecturers - contact your local SAGE representative to discuss your course needs or to request an inspection copy.Randall E. Schumacker's comprehensive book describes in detail the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker's text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling.