Statistical Data Analytics
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Introduction To Statistics And Data Analysis
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Author : Christian Heumann
language : en
Publisher: Springer Nature
Release Date : 2023-01-30
Introduction To Statistics And Data Analysis written by Christian Heumann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-30 with Mathematics categories.
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
Statistical Data Analysis Handbook
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Author : Francis J. Wall
language : en
Publisher: McGraw-Hill Companies
Release Date : 1986
Statistical Data Analysis Handbook written by Francis J. Wall and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Mathematics categories.
It must be emphasized that this is not a text book on statistics. Instead it is a working tool that presents data analysis in clear, concise terms which can be readily understood even by those without formal training in statistics. Following pivotal chapters on the art of analysis, you will find two invaluable reference sections to which you're bound to turn again and again as you make your analyses. The first section gives you the data analyst's-as opposed to the statistician's-eyeview of the basics of a number of fundamental statistical techniques, including random samples, p-values, the analysis of variance, statistical tests, and testing. The second gives you 20 statistical tables that have been especially formatted and expanded to make them far easier to read and apply than conventional statistical tables.
Statistical Data Analytics
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Author : Walter W. Piegorsch
language : en
Publisher: John Wiley & Sons
Release Date : 2016-03-22
Statistical Data Analytics written by Walter W. Piegorsch 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 2016-03-22 with Mathematics categories.
Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.
Statistical Data Analysis Based On The L B1 S Norm And Related Methods
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Author : Yadolah Dodge
language : en
Publisher: Springer Science & Business Media
Release Date : 2002
Statistical Data Analysis Based On The L B1 S Norm And Related Methods written by Yadolah Dodge 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 2002 with Mathematics categories.
This volume contains a selection of invited papers, presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in Neuchâtel, Switzerland, from August 4–9, 2002. The contributions represent a clear evidence to the importance of development of theory, methods and applications related to the statistical data analysis based on the L1-norm.
Statistics Data Analysis And Decision Modeling
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Author : James Robert Evans
language : en
Publisher: Prentice Hall
Release Date : 2007
Statistics Data Analysis And Decision Modeling written by James Robert Evans and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Business & Economics categories.
This book covers basic concepts of business statistics, data analysis, and management science in a spreadsheet environment. Practical applications are emphasized throughout the book for business decision-making; a comprehensive database is developed, with marketing, financial, and production data already formatted on Excel worksheets. This shows how real data is used and decisions are made. Using Excel as the basic software, and including such add-ins as PHStat2, Crystal Ball, and TreePlan, this book covers a wide variety of topics related to business statistics: statistical thinking in business; displaying and summarizing data; random variables; sampling; regression analysis; forecasting; statistical quality control; risk analysis and Monte-Carlo simulation; systems simulation modeling and analysis; selection models and decision analysis; optimization modeling; and solving and analyzing optimization models. For those employed in the fields of quality control, management science, operations management, statistical science, and those who need to interpret data to make informed business decisions.
An Introduction To Statistics And Data Analysis Using Stata
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Author : Lisa Daniels
language : en
Publisher: SAGE Publications
Release Date : 2019-01-11
An Introduction To Statistics And Data Analysis Using Stata written by Lisa Daniels and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-11 with Social Science categories.
An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.
Business Analytics Using R A Practical Approach
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Author : Umesh R Hodeghatta
language : en
Publisher: Apress
Release Date : 2016-12-27
Business Analytics Using R A Practical Approach written by Umesh R Hodeghatta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-27 with Computers categories.
Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictiveanalytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.
Statistical Data Analysis Based On The L1 Norm And Related Methods
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Author : Yadolah Dodge
language : en
Publisher: Birkhäuser
Release Date : 2012-11-01
Statistical Data Analysis Based On The L1 Norm And Related Methods written by Yadolah Dodge and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-01 with Mathematics categories.
This volume contains a selection of invited papers, presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in Neuchâtel, Switzerland, from August 4–9, 2002. The contributions represent clear evidence to the importance of the development of theory, methods and applications related to the statistical data analysis based on the L1-norm.
Statistical Data Analytics
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Author : Walter W. Piegorsch
language : en
Publisher: John Wiley & Sons
Release Date : 2015-07-01
Statistical Data Analytics written by Walter W. Piegorsch 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 2015-07-01 with Mathematics categories.
Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.
Data Analytics For The Social Sciences
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Author : G. David Garson
language : en
Publisher: Routledge
Release Date : 2021-11-29
Data Analytics For The Social Sciences written by G. David Garson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Psychology categories.
Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.