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Statistics All-in-One For Dummies
by Deborah J. RumseyThe odds-on best way to master stats. Statistics All-in-One For Dummies is packed with lessons, examples, and practice problems to help you slay your stats course. Develop confidence and understanding in statistics with easy-to-understand (even fun) explanations of key concepts. Plus, you’ll get access to online chapter quizzes and other resources that will turn you into a stats master. This book teaches you how to interpret graphs, determine probability, critique data, and so much more. Written by an expert author and serious statistics nerd, Statistics AIO For Dummies explains everything in terms anyone can understand. Get a grasp of basic statistics concepts required in every statistics course Clear up the process of interpreting graphs, understanding polls, and analyzing data Master correlation, regression, and other data analysis tools Score higher on stats tests and get a better grade in your high school or college classStatistics All-in-One For Dummies follows the curriculum of intro college statistics courses (including AP Stats!) so you can learn everything you need to know to get the grade you need—the Dummies way.
Statistics Done Wrong
by Alex ReinhartScientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong.Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics.You'll find advice on:–Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan–How to think about p values, significance, insignificance, confidence intervals, and regression–Choosing the right sample size and avoiding false positives–Reporting your analysis and publishing your data and source code–Procedures to follow, precautions to take, and analytical software that can helpScientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know.The first step toward statistics done right is Statistics Done Wrong.
Statistics For Business And Economics
by Terry Sincich P. George Benson James McClaveThirteenth Edition, Statistics for Business and Economics introduces statistics in the context of contemporary business. Emphasizing statistical literacy in thinking, the text applies its concepts with real data and uses technology to develop a deeper conceptual understanding. Examples, activities, and case studies foster active learning while emphasizing intuitive concepts of probability and teaching readers to make informed business decisions. The Thirteenth Edition continues to highlight the importance of ethical behavior in collecting, interpreting, and reporting on data, while also providing a wealth of new and updated exercises and case studies.
Statistics For Business: Decision Making And Analysis
by Robert A. Stine Dean P. FosterUnderstand Business. Understand Data. The 3rd Edition of Statistics for Business: Decision Making and Analysis emphasizes an application-based approach, in which readers learn how to work with data to make decisions. In this contemporary presentation of business statistics, readers learn how to approach business decisions through a 4M Analytics decision making strategy—motivation, method, mechanics and message—to better understand how a business context motivates the statistical process and how the results inform a course of action. Each chapter includes hints on using Excel, Minitab Express, and JMP for calculations, pointing the reader in the right direction to get started with analysis of data.
Statistics Tables: For Mathematicians, Engineers, Economists and the Behavioural and Management Sciences
by Henry R. NeaveFor three decades, Henry Neave’s Statistics Tables has been the gold standard for all students taking an introductory statistical methods course as part of their wider degree in a host of disciplines including mathematics, economics, business and management, geography and psychology. The period has seen a large increase in the level of mathematics and statistics required to achieve these qualifications and Statistics Tables has helped several generations of students meet their goals. All the features of the first edition are retained including the full range of best-known standard statistical techniques, as well as some lesser-known methods that can be hard to track down elsewhere. The explanatory introductions to each section have been updated and the second edition benefits from the inclusion of a valuable and comprehensive new section on an approach to simple but powerful investigation of process data. This will help the book continue in its position as the prime statistical reference for all students of mathematics, engineering and the social sciences, and everyone who needs effective methods for analysing data.
Statistics and Data Analysis for Financial Engineering
by David Ruppert David S. MattesonThe new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.
Statistics and Data Visualization Using R: The Art and Practice of Data Analysis
by David S. BrownDesigned to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of Data Analysis by David S. Brown teaches students statistics through charts, graphs, and displays of data that help students develop intuition around statistics as well as data visualization skills. By focusing on the visual nature of statistics instead of mathematical proofs and derivations, students can see the relationships between variables that are the foundation of quantitative analysis. Using the latest tools in R and R RStudio® for calculations and data visualization, students learn valuable skills they can take with them into a variety of future careers in the public sector, the private sector, or academia. Starting at the most basic introduction to data and going through most crucial statistical methods, this introductory textbook quickly gets students new to statistics up to speed running analyses and interpreting data from social science research.
Statistics and Data Visualization Using R: The Art and Practice of Data Analysis
by David S. BrownDesigned to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of Data Analysis by David S. Brown teaches students statistics through charts, graphs, and displays of data that help students develop intuition around statistics as well as data visualization skills. By focusing on the visual nature of statistics instead of mathematical proofs and derivations, students can see the relationships between variables that are the foundation of quantitative analysis. Using the latest tools in R and R RStudio® for calculations and data visualization, students learn valuable skills they can take with them into a variety of future careers in the public sector, the private sector, or academia. Starting at the most basic introduction to data and going through most crucial statistical methods, this introductory textbook quickly gets students new to statistics up to speed running analyses and interpreting data from social science research.
Statistics and Decisions: An Introduction to Foundations
by S. H. KimThis book provides the necessary prerequisites in probability and statistics as well as the key ideas in decision theory. It is helpful to students and practitioners who desire to apply decision-theoretic thinking to their own work.
Statistics and Machine Learning Methods for EHR Data: From Data Extraction to Data Analytics (Chapman & Hall/CRC Healthcare Informatics Series)
by Hulin Wu Jose-Miguel Yamal Ashraf Yaseen Vahed MaroufyThe use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.
Statistics for Business
by Derek L. WallerStatistics for Business explains the fundamentals of statistical analysis in a lucid, pragmatic way. A thorough knowledge of statistics is essential for decision making in all corners of business and management. By collecting, organizing and analyzing statistical data you can express what you know, benchmark your current situation, and estimate future outcomes. Based entirely on Microsoft Excel, this book covers a spectrum of statistic fundamentals from basic principles, to probability, sampling, hypothesis testing, forecasting, statistical process control and six-sigma management. This second edition is packed with features to aid understanding and help ensure that every aspect of your knowledge of statistics is applicable to practice, including: Icebreakers introducing each chapter that relate statistics to the real world, drawn from management and hospitality situations Detailed worked examples in each chapter Over 140 case-exercises complete with objective, situation, requirements, and answers A complete glossary of key terminology and formulas, mathematical relationships, and Excel relationships and functions A brand new companion website containing slides, worked-out-solutions to the case-exercises, and a test bank With a clear and accessible style this book makes statistics easier to understand. It is ideal for business, management, tourism and hospitality students who want to learn how to apply statistics to the real world.
Statistics for Business
by Derek WallerStatistical analysis is essential to business decision-making and management, but the underlying theory of data collection, organization and analysis is one of the most challenging topics for business students and practitioners. This user-friendly text and CD-ROM package will help you to develop strong skills in presenting and interpreting statistical information in a business or management environment. Based entirely on using Microsoft Excel rather than more complicated applications, it includes a clear guide to using Excel with the key functions employed in the book, a glossary of terms and equations, plus a section specifically for those readers who feel rusty in basic maths. Each chapter has worked examples and explanations to illustrate the use of statistics in real life scenarios, with databases for the worked examples, cases and answers on the accompanying CD-ROM.
Statistics for Business
by Perumal MariappanStatistics for Business is meant as a textbook for students in business, computer science, bioengineering, environmental technology, and mathematics. In recent years, business statistics is used widely for decision making in business endeavours. It emphasizes statistical applications, statistical model building, and determining the manual solution methods. Special Features: This text is prepared based on "self-taught" method. For most of the methods, the required algorithm is clearly explained using flow-charting methodology. More than 200 solved problems provided. More than 175 end-of-chapter exercises with answers are provided. This allows teachers ample flexibility in adopting the textbook to their individual class plans. This textbook is meant to for beginners and advanced learners as a text in Statistics for Business or Applied Statistics for undergraduate and graduate students.
Statistics for Business and Economics (Special Edition)
by David R. Anderson Dennis J. Sweeney Thomas A. Williams Jeffrey D. CammStatistics for Business and Economics by Jeffrey D. Camm, Thomas A. Williams, Dennis J. Sweeney, and David R. Anderson.
Statistics for Business and Financial Economics
by Cheng-Few Lee John C. Lee Alice C. LeeStatistics for Business and Financial Economics, 3rd edition is the definitive Business Statistics book to use Finance, Economics, and Accounting data throughout the entire book. Therefore, this book gives students an understanding of how to apply the methodology of statistics to real world situations. In particular, this book shows how descriptive statistics, probability, statistical distributions, statistical inference, regression methods, and statistical decision theory can be used to analyze individual stock price, stock index, stock rate of return, market rate of return, and decision making. In addition, this book also shows how time-series analysis and the statistical decision theory method can be used to analyze accounting and financial data. In this fully-revised edition, the real world examples have been reconfigured and sections have been edited for better understanding of the topics.
Statistics for Finance (Chapman & Hall/CRC Texts in Statistical Science)
by Henrik Madsen Erik Lindström Jan Nygaard NielsenStatistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Itō’s formula, the Black–Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives, identify interest rate models, value bonds, estimate parameters, and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues. In addition, end-of-chapter exercises develop students’ financial reasoning skills.
Statistics for Health Data Science: An Organic Approach (Springer Texts in Statistics)
by Ruth Etzioni Micha Mandel Roman GulatiStudents and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students’ anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/
Statistics for Innovation I: SIS 2025, Short Papers, Plenary, Specialized, and Solicited Sessions (Italian Statistical Society Series on Advances in Statistics)
by Enrico Di Bella Vincenzo Gioia Corrado Lagazio Susanna ZaccarinThis book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society&’s international conference on &“Statistics for Innovation&”, SIS 2025, held in Genoa, Italy, June 16-18, 2025. It is the first of four volumes, featuring invited contributions presented in the Plenary, Specialized and Solicited Sessions. Providing a comprehensive overview of innovations in modern statistical methods and applications, the volumes address a large number of topics of current interest, contributing to a rapid dissemination of quantitative methods for data analysis across the various fields of scientific research and social life. The volumes underpin the role of statistics and data science in fostering innovation in numerous fields, including business, industry, finance, technology, environment, health and medicine, official statistics, public policy, welfare, social issues and sustainable development. One of the aims of the Italian Statistical Society (SIS) is to promote scientific activities for the development of statistical sciences. Together with the biennial international Scientific Meeting, the intermediate international statistical conferences on a particular topic of interest represent the Society&’s most important events which bring together national and international researchers and professionals to exchange ideas and discuss recent advances and developments in theoretical and applied statistics.
Statistics for Innovation II: SIS 2025, Short Papers, Contributed Sessions 1 (Italian Statistical Society Series on Advances in Statistics)
by Enrico Di Bella Vincenzo Gioia Corrado Lagazio Susanna ZaccarinThis book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society&’s international conference on &“Statistics for Innovation&”, SIS 2025, held in Genoa, Italy, June 16-18, 2025. It is the second of four volumes, featuring the first part of the contributions presented in the Contributed Sessions. Providing a comprehensive overview of innovations in modern statistical methods and applications, the volumes address a large number of topics of current interest, contributing to a rapid dissemination of quantitative methods for data analysis across the various fields of scientific research and social life. The volumes underpin the role of statistics and data science in fostering innovation in numerous fields, including business, industry, finance, technology, environment, health and medicine, official statistics, public policy, welfare, social issues and sustainable development. One of the aims of the Italian Statistical Society (SIS) is to promote scientific activities for the development of statistical sciences. Together with the biennial international Scientific Meeting, the intermediate international statistical conferences on a particular topic of interest represent the Society&’s most important events which bring together national and international researchers and professionals to exchange ideas and discuss recent advances and developments in theoretical and applied statistics.
Statistics for Innovation III: SIS 2025, Short Papers, Contributed Sessions 2 (Italian Statistical Society Series on Advances in Statistics)
by Enrico Di Bella Vincenzo Gioia Corrado Lagazio Susanna ZaccarinThis book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society&’s international conference on &“Statistics for Innovation&”, SIS 2025, held in Genoa, Italy, June 16-18, 2025. It is the third of four volumes, featuring the second part of the contributions presented in the Contributed Sessions. Providing a comprehensive overview of innovations in modern statistical methods and applications, the volumes address a large number of topics of current interest, contributing to a rapid dissemination of quantitative methods for data analysis across the various fields of scientific research and social life. The volumes underpin the role of statistics and data science in fostering innovation in numerous fields, including business, industry, finance, technology, environment, health and medicine, official statistics, public policy, welfare, social issues and sustainable development. One of the aims of the Italian Statistical Society (SIS) is to promote scientific activities for the development of statistical sciences. Together with the biennial international Scientific Meeting, the intermediate international statistical conferences on a particular topic of interest represent the Society&’s most important events which bring together national and international researchers and professionals to exchange ideas and discuss recent advances and developments in theoretical and applied statistics.
Statistics for Innovation IV: SIS 2025, Short Papers, Contributed Sessions 3 (Italian Statistical Society Series on Advances in Statistics)
by Enrico Di Bella Vincenzo Gioia Corrado Lagazio Susanna ZaccarinThis book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society&’s international conference on &“Statistics for Innovation&”, SIS 2025, held in Genoa, Italy, June 16-18, 2025. It is the last of four volumes, featuring the third part of the contributions presented in the Contributed Sessions. Providing a comprehensive overview of innovations in modern statistical methods and applications, the volumes address a large number of topics of current interest, contributing to a rapid dissemination of quantitative methods for data analysis across the various fields of scientific research and social life. The volumes underpin the role of statistics and data science in fostering innovation in numerous fields, including business, industry, finance, technology, environment, health and medicine, official statistics, public policy, welfare, social issues and sustainable development. One of the aims of the Italian Statistical Society (SIS) is to promote scientific activities for the development of statistical sciences. Together with the biennial international Scientific Meeting, the intermediate international statistical conferences on a particular topic of interest represent the Society&’s most important events which bring together national and international researchers and professionals to exchange ideas and discuss recent advances and developments in theoretical and applied statistics.
Statistics for Managers Using Microsoft Excel
by David Levine David Stephan Kathryn Szabat<p>For undergraduate business statistics courses. Analyzing the Data Applicable to Business. This text is the gold standard for learning how to use Microsoft Excel® in business statistics, helping students gain the understanding they need to be successful in their careers. The authors present statistics in the context of specific business fields; full chapters on business analytics further prepare students for success in their professions. Current data throughout the text lets students practice analyzing the types of data they will see in their professions. The friendly writing style include tips throughout to encourage learning. <p>The book also integrates PHStat, an add-in that bolsters the statistical functions of Excel.</p>
Statistics for Marketing and Consumer Research
by Mario MazzocchiBalancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied. The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including: - 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots) - 136 multiple choice questions for tests This is augmented by in-depth discussion of topics including: - Sampling - Data management and statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling
Statistics for Non-Statisticians
by Birger MadsenThis book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes. The book is untraditional, both with respect to the choice of topics and the presentation. The topics were determined by what is most useful for practical statistical work: even experienced statisticians will find new topics or new approaches to traditional topics. The presentation is as non-mathematical as possible. Mathematical formulae are presented only if they are necessary for calculations and/or add to readers' understanding. A sample survey is developed as a realistic example throughout the book, and many further examples are presented, which also use data spreadsheets from a supplementary website.
Statistics for Public Policy: A Practical Guide to Being Mostly Right (or at Least Respectably Wrong)
by Jeremy G. WeberA long-overdue guide on how to use statistics to bring clarity, not confusion, to policy work. Statistics are an essential tool for making, evaluating, and improving public policy. Statistics for Public Policy is a crash course in wielding these unruly tools to bring maximum clarity to policy work. Former White House economist Jeremy G. Weber offers an accessible voice of experience for the challenges of this work, focusing on seven core practices: Thinking big-picture about the role of data in decisions Critically engaging with data by focusing on its origins, purpose, and generalizability Understanding the strengths and limits of the simple statistics that dominate most policy discussions Developing reasons for considering a number to be practically small or large Distinguishing correlation from causation and minor causes from major causes Communicating statistics so that they are seen, understood, and believed Maintaining credibility by being right (or at least respectably wrong) in every setting Statistics for Public Policy dispenses with the opacity and technical language that have long made this space impenetrable; instead, Weber offers an essential resource for all students and professionals working at the intersections of data and policy interventions. This book is all signal, no noise.