Introduction To R Software
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An Introduction To R
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Author : William N. Venables
language : en
Publisher: Network Theory.
Release Date : 2002
An Introduction To R written by William N. Venables and has been published by Network Theory. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
Provides a tutorial guide to GNU R, a software environment for statistical computing and graphics.
Moving From Ibm Spss To R And Rstudio
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Author : Howard T. Tokunaga
language : en
Publisher: SAGE Publications
Release Date : 2021-02-12
Moving From Ibm Spss To R And Rstudio written by Howard T. Tokunaga and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-12 with Psychology categories.
Are you a researcher or instructor who has been wanting to learn R and RStudio®, but you don′t know where to begin? Do you want to be able to perform all the same functions you use in IBM® SPSS® in R? Is your license to IBM® SPSS® expiring, or are you looking to provide your students guidance to a freely-available statistical software program? Moving from IBM® SPSS® to R and RStudio®: A Statistics Companion is a concise and easy-to-read guide for users who want to know learn how to perform statistical calculations in R. Brief chapters start with a step-by-step introduction to R and RStudio, offering basic installation information and a summary of the differences. Subsequent chapters walk through differences between SPSS and R, in terms of data files, concepts, and structure. Detailed examples provide walk-throughs for different types of data conversions and transformations and their equivalent in R. Helpful and comprehensive appendices provide tables of each statistical transformation in R with its equivalent in SPSS and show what, if any, differences in assumptions factor to into each function. Statistical tests from t-tests to ANOVA through three-factor ANOVA and multiple regression and chi-square are covered in detail, showing each step in the process for both programs. By focusing just on R and eschewing detailed conversations about statistics, this brief guide gives adept SPSS® users just the information they need to transition their data analyses from SPSS to R.
Modern Actuarial Risk Theory
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Author : Rob Kaas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-03
Modern Actuarial Risk Theory written by Rob Kaas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-03 with Business & Economics categories.
Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and.
Information Quality
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Author : Ron S. Kenett
language : en
Publisher: John Wiley & Sons
Release Date : 2016-10-13
Information Quality written by Ron S. Kenett and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-13 with Mathematics categories.
Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.
Introduction To Statistical Methods For Financial Models
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Author : Thomas A Severini
language : en
Publisher: CRC Press
Release Date : 2017-07-06
Introduction To Statistical Methods For Financial Models written by Thomas A Severini and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Business & Economics categories.
This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.
Introduction To Linear Regression Analysis
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Author : Douglas C. Montgomery
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-06
Introduction To Linear Regression Analysis written by Douglas C. Montgomery and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-06 with Mathematics categories.
Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.
Introduction To Statistical Data Analysis For The Life Sciences
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Author : Claus Thorn Ekstrom
language : en
Publisher: CRC Press
Release Date : 2014-11-06
Introduction To Statistical Data Analysis For The Life Sciences written by Claus Thorn Ekstrom and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-06 with Mathematics categories.
A Hands-On Approach to Teaching Introductory StatisticsExpanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the m
Introduction To Research Methods And Data Analysis In The Health Sciences
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Author : Gareth Hagger-Johnson
language : en
Publisher: Routledge
Release Date : 2014-06-20
Introduction To Research Methods And Data Analysis In The Health Sciences written by Gareth Hagger-Johnson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-20 with Medical categories.
Whilst the ‘health sciences’ are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences – and students are expected increasingly to do both. Introduction to Research Methods and Data Analysis in the Health Sciences presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis. Divided into the three strands that run throughout quantitative health science research – critical numbers, critical appraisal of existing research, and conducting new research – this accessible textbook introduces: Descriptive statistics Measures of association for categorical and continuous outcomes Confounding, effect modification, mediation and causal inference Critical appraisal Searching the literature Randomised controlled trials Cohort studies Case-control studies Research ethics and data management Dissemination and publication Linear regression for continuous outcomes Logistic regression for categorical outcomes. A dedicated companion website offers additional teaching and learning resources for students and lecturers, including screenshots, R programming code, and extensive self-assessment material linked to the book’s exercises and activities. Clear and accessible with a comprehensive coverage to equip the reader with an understanding of the research process and the practical skills they need to collect and analyse data, it is essential reading for all undergraduate and postgraduate students in the health and medical sciences.
Biostatistics For Clinical And Public Health Research
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Author : Melody S. Goodman
language : en
Publisher: Taylor & Francis
Release Date : 2025-08-19
Biostatistics For Clinical And Public Health Research written by Melody S. Goodman and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-19 with Medical categories.
The new edition of Biostatistics for Clinical and Public Health Research is an introductory workbook to provide not only a concise overview of key statistical concepts but also step-by-step guidance on how to apply these through a range of software packages, including R, SAS, and Stata. Providing a comprehensive survey of essential topics – including probability, diagnostic testing, probability distributions, estimation, hypothesis testing, correlation, regression, and survival analysis – each chapter features a detailed summary of the topic at hand, followed by examples to show readers how to conduct analysis and interpret the results. Also including exercises and solutions, case studies, take-away points, and data sets (Excel, SAS, and Stata formats), the new edition now includes a chapter on data literacy and data ethics, as well as examples drawn from the COVID-19 pandemic. Ideally suited to accompany either a course or as support for independent study, this book will be an invaluable tool for both students of biostatistics and clinical or public health practitioners.
Statistical Methods For Global Health And Epidemiology
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Author : Xinguang Chen
language : en
Publisher: Springer Nature
Release Date : 2020-04-13
Statistical Methods For Global Health And Epidemiology written by Xinguang Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-13 with Medical categories.
This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health and epidemiology involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, cancer, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective; addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers with methods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation.