Statistical Data Analysis Explained
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Statistical Data Analysis Explained
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Author : Clemens Reimann
language : en
Publisher: John Wiley & Sons
Release Date : 2011-08-31
Statistical Data Analysis Explained written by Clemens Reimann 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 2011-08-31 with Science categories.
Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.
Data Analysis Explained
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Author : David W. Gerbing
language : en
Publisher:
Release Date : 2013
Data Analysis Explained written by David W. Gerbing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. Dr. Gerbing introduces R through less R which allows readers to learn how to organize data for analysis, read the data into R, and produce output, without performing programming exercises first. The text reviews basic statistical procedures with the lessR enhancements added to the standard R environment. Through the use of lessR, R becomes immediately accessible to the novice user. An ideal supplement for graduate or advanced undergraduate courses in statistics, research methods, or any course in which R is used.
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.
Statistics Data Analysis And Decision Modeling
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Author : James Robert Evans
language : en
Publisher:
Release Date : 2003
Statistics Data Analysis And Decision Modeling written by James Robert Evans and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 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.
R Programming
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Author : Kingsley Okoye
language : en
Publisher: Springer Nature
Release Date : 2024-07-07
R Programming written by Kingsley Okoye and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-07 with Computers categories.
This book is written for statisticians, data analysts, programmers, researchers, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using R object-oriented programming language and RStudio integrated development environment (IDE). R is an open-source software with a development environment (RStudio) for computing statistics and graphical displays through data manipulation, modeling, and calculation. R packages and supported libraries provide a wide range of functions for programming and analyzing of data. Unlike many of the existing statistical software, R has the added benefit of allowing the users to write more efficient codes by using command-line scripting and vectors. It has several built-in functions and libraries that are extensible and allows the users to define their own (customized) functions on how they expect the program to behave while handling the data, which can also be stored in the simple object system. Therefore, this book serves as both textbook and manual for R statistics particularly in academic research, data analytics, and computer programming targeted to help inform and guide the work of the users. It provides information about different types of statistical data analysis and methods, and the best scenarios for use of each case in R. It gives a hands-on step-by-step practical guide on how to identify and conduct the different parametric and nonparametric procedures. This includes a description of the different conditions or assumptions that are necessary for performing the various statistical methods or tests, and how to understand the results of the methods. The book also covers the different data formats and sources, and how to test for the reliability and validity of the available datasets. Different research experiments, case scenarios, and examples are explained in this book. The book provides a comprehensive description and step-by-step practical hands-on guide to carrying out the different types of statistical analysis in R particularly for research purposes with examples. Ranging from how to import and store datasets in R as objects, how to code and call the methods or functions for manipulating the datasets or objects, factorization, and vectorization, to better reasoning, interpretation, and storage of the results for future use, and graphical visualizations and representations thus congruence of Statistics and Computer programming in Research.
Data Analysis And Regression
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Author : Frederick Mosteller
language : en
Publisher: Pearson
Release Date : 1977
Data Analysis And Regression written by Frederick Mosteller and has been published by Pearson this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Mathematics categories.
Textbook on statistical analysis and data analysis - presents practical evaluation techniques, focusing on the computing and graphical fitting of regression. Bibliography after each chapter and statistical tables.
Statistical Data Analysis For Ocean And Atmospheric Sciences
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Author : H. J. Thiébaux
language : en
Publisher: Academic Press
Release Date : 1994-11-07
Statistical Data Analysis For Ocean And Atmospheric Sciences written by H. J. Thiébaux and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-11-07 with Mathematics categories.
Studies of local and global phenomena generate descriptions which require statistical analysis. In this text, H. Jean Thiebaux presents a succinct yet comprehensive review of the fundamentals of statistics as they pertain to studies in oceanic and atmospheric sciences. The text includes an accompanying disk with compatible Minitab sample data. Together, this volume and the included data provide insights into the basics of statistical inference, data analysis, and distributional models of variability. Oceanographers, meteorologists, marine biologists, and other environmental scientists will find this book of great value as a statistical tool for their continuing studies. Specifically designed for students of the ocean and atmospheric sciences Contains a disk containing files of real ocean and atmospheric data, in universal ASCII format, on which many of the exercises are based Provides succinct yet comprehensive coverage Designed to teach students statistical methods with the scientific realism of computer analysis and statistical inference
The Art Of Data Analysis
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Author : Kristin H. Jarman
language : en
Publisher: John Wiley & Sons
Release Date : 2013-04-17
The Art Of Data Analysis written by Kristin H. Jarman 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 2013-04-17 with Mathematics categories.
A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.
Proceedings Of The Section On Statistical Education
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Author : American Statistical Association. Section on Statistical Education
language : en
Publisher:
Release Date : 1984
Proceedings Of The Section On Statistical Education written by American Statistical Association. Section on Statistical Education and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Educational statistics categories.
Introduction To Statistical Data Analysis For The Life Sciences Second Edition
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Author : Claus Thorn Ekstrom
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2017-11-15
Introduction To Statistical Data Analysis For The Life Sciences Second Edition written by Claus Thorn Ekstrom and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-15 with categories.
A Hands-On Approach to Teaching Introductory Statistics Expanded 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 mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets. New to the Second Edition A new chapter on non-linear regression models A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken Additional exercises in most chapters A summary of statistical formulas related to the specific designs used to teach the statistical concepts This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.