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Author: Barry Glaz Publisher: John Wiley & Sons ISBN: 0891183590 Category : Technology & Engineering Languages : en Pages : 672
Book Description
Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.
Author: Barry Glaz Publisher: John Wiley & Sons ISBN: 0891183590 Category : Technology & Engineering Languages : en Pages : 672
Book Description
Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.
Author: Dieter Rasch Publisher: John Wiley & Sons ISBN: 1119551544 Category : Mathematics Languages : en Pages : 719
Book Description
Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.
Author: Rebecca M. Warner Publisher: SAGE ISBN: 141299134X Category : Mathematics Languages : en Pages : 1209
Book Description
Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
Author: Mehmet Ali Arslan Publisher: ISBN: 9780999200513 Category : Languages : en Pages :
Book Description
The first edition of Applied Statistics and DOE is truly an exceptional book, emphasizing coverage on the main subjects of statistics with hands-on application content including; collection/presentation of data, descriptive/inferential statistics in analyzing the data, input/output causal transfer function building with regression analysis, statistical process control(SPC) through control charts and process capability analysis. Further, the textbook gives an excellent insight about Design of Experiments(DOE) and introduces OFAT, factorial and Taguchi designs in comparative detail. The textbook is specially written for the use of all levels of students from different backgrounds and also designed to equip them with every day use of hands-on knowledge and experience in handling numerous statistical and DOE problems.
Author: D. R. Cox Publisher: Cambridge University Press ISBN: 1139503545 Category : Mathematics Languages : en Pages : 213
Book Description
Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.
Author: Eric Goh Ming Hui Publisher: Apress ISBN: 1484242009 Category : Computers Languages : en Pages : 254
Book Description
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will LearnDiscover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.
Author: Christopher A. Janicak Publisher: Rowman & Littlefield ISBN: 1636713807 Category : Technology & Engineering Languages : en Pages : 227
Book Description
This completely updated fourth edition is designed to provide safety professionals or those studying to become safety professionals with the basic methods and principles necessary to apply statistics properly. Safety professionals often encounter statistics in the literature they read and are required to present findings or make decisions based on data analyses. Statistics can be used to justify the implementation of a program, identify areas that need to be addressed, or justify the impact that various safety programs have on losses and accidents. Safety professionals also use a variety of data in their day-to-day work. Applied Statistics in Occupational Safety and Health presents the reader with practical information to make their job easier. In addition to sample problems and solutions, the authors include easy-to-read charts and tables, appendices containing statistical tables, and a glossary of terms.
Author: Mehmet Mehmetoglu Publisher: SAGE ISBN: 1529788463 Category : Social Science Languages : en Pages : 421
Book Description
Straightforward, clear, and applied, this book will give you the theoretical and practical basis you need to apply data analysis techniques to real data. Combining key statistical concepts with detailed technical advice, it addresses common themes and problems presented by real research, and shows you how to adjust your techniques and apply your statistical knowledge to a range of datasets. It also embeds code and software output throughout and is supported by online resources to enable practice and safe experimentation. The book includes: · Original case studies and data sets · Practical exercises and lists of commands for each chapter · Downloadable Stata programmes created to work alongside chapters · A wide range of detailed applications using Stata · Step-by-step guidance on writing the relevant code. This is the perfect text for anyone doing statistical research in the social sciences getting started using Stata for data analysis.
Author: Eelko Huizingh Publisher: SAGE ISBN: 1446223000 Category : Social Science Languages : en Pages : 368
Book Description
Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text′s self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers : 1. A self-study guide for learning how to use SPSS. 2. A reference guide for selecting the appropriate statistical technique and a stepwise do-it-yourself guide for analysing data and interpreting the results. 3. Readers of the book can download the SPSS data file that is used for most of the examples throughout the book. Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.
Author: Barry Glaz
Author: Barry Glaz
Author: Dieter Rasch
Author: Rebecca M. Warner
Author: Mehmet Ali Arslan
Author: W. N. Venables
Author: D. R. Cox
Author: Eric Goh Ming Hui
Author: Christopher A. Janicak
Author: Mehmet Mehmetoglu
Author: Eelko Huizingh