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1. |
Record Nr. |
UNINA9910963680003321 |
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Autore |
Gardener Mark |
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Titolo |
Beginning R : the statistical programming language / / Mark Gardener |
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Pubbl/distr/stampa |
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Indianapolis, : John Wiley & Sons, 2012 |
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ISBN |
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9786613661579 |
9781280684630 |
1280684631 |
9781118226162 |
111822616X |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (507 p.) |
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Collana |
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Wrox programmer to programmer |
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Disciplina |
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Soggetti |
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R (Computer program language) |
Statistics - Data processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Beginning R; Contents; Introduction; Who This Book Is For; What This Book Covers; How This Book Is Structured; What You Need to Use This Book; Conventions; Source Code; Errata; p2p.wrox.com; Chapter 1: Introducing R: What It Is and How to Get It; Getting the Hang of R; Running the R Program; Finding Your Way with R; Command Packages; Summary; Chapter 2: Starting Out: Becoming Familiar with R; Some Simple Math; Reading and Getting Data into R; Viewing Named Objects; Types of Data Items; The Structure of Data Items; Examining Data Structure; Working with History Commands; Saving Your Work in R |
SummaryChapter 3: Starting Out: Working; Manipulating Objects; Viewing Objects within Objects; Constructing Data Objects; Forms of Data Objects: Testing and Converting; Summary; Chapter 4: Data: Descriptive Statistics and Tabulation; Summary Commands; Summarizing Samples; Summary Tables; Summary; Chapter 5: Data: Distribution; Looking at the Distribution of Data; Summary; Chapter 6: Simple Hypothesis Testing; Using the Student's t-test; The Wilcoxon U-Test (Mann-Whitney); Paired t- and U-Tests; Correlation and Covariance; Tests for Association; Summary |
Chapter 7: Introduction to Graphical AnalysisBox-whisker Plots; Scatter |
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Plots; Pairs Plots (Multiple Correlation Plots); Line Charts; Pie Charts; Cleveland Dot Charts; Bar Charts; Copy Graphics to Other Applications; Summary; Chapter 8: Formula Notation and Complex Statistics; Examples of Using Formula Syntax for Basic Tests; Formula Notation in Graphics; Analysis of Variance (ANOVA); Summary; Chapter 9: Manipulating Data and Extracting Components; Creating Data for Complex Analysis; Summarizing Data; Summary; Chapter 10: Regression (Linear Modeling); Simple Linear Regression |
Multiple RegressionCurvilinear Regression; Plotting Linear Models and Curve Fitting; Summarizing Regression Models; Summary; Chapter 11: More About Graphs; Adding Elements to Existing Plots; Matrix Plots (Multiple Series on One Graph); Multiple Plots in One Window; Exporting Graphs; Summary; Chapter 12: Writing Your Own Scripts: Beginning to Program; Copy and Paste Scripts; Creating Simple Functions; Making Source Code; Summary; Appendix: Answers to Exercises; Chapter 1; Chapter 2; Chapter 3; Chapter 4; Chapter 5; Chapter 6; Chapter 7; Chapter 8; Chapter 9; Chapter 10; Chapter 11; Chapter 12 |
IndexAdvertisement |
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Sommario/riassunto |
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Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex s |
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2. |
Record Nr. |
UNIORUON00169473 |
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Titolo |
Ancient scepticism and the sceptical tradition / edited by Juha Sihvola |
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Pubbl/distr/stampa |
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Helsinki, : The Philosophical Society of Finland, 2000 |
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ISBN |
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Descrizione fisica |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
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Livello bibliografico |
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3. |
Record Nr. |
UNINA9910993871703321 |
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Autore |
Xu Jin |
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Titolo |
Biological Computing / / by Jin Xu |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (XVII, 329 p. 144 illus., 110 illus. in color.) |
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Disciplina |
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Soggetti |
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Computer science |
Computer systems |
Computers |
Models of Computation |
Computer System Implementation |
Hardware Performance and Reliability |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1 Introduction -- Chapter 2 Graphs and Computational |
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Complexity -- Chapter 3 Biocomputing -- Data -- Chapter 4 Biological Computing Operators -- Enzymes and Biochemical Operations -- Chapter 5 DNA Coding Theory and Algorithms -- Chapter 6 Enumerative DNA Computing Model -- Chapter 7 Non-enumerative DNA Computing Model for Graph Vertex Coloring -- Chapter 8 Parallel Vertex Coloring DNA Computing Model -- Chapter 9 Probe Machine -- Chapter 10 DNA Algorithmic Self-Assembly -- Chapter 11 RNA Computing -- Chapter 12 Protein Computing. |
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Sommario/riassunto |
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This open access book comprehensively introduces biocomputing, focusing on its foundational theories, experimental operations, and computational models. Biocomputing represents an innovative computational paradigm that leverages biomolecules as a carrier for processing and storing information. As a core enabler of human progress, computational tools serve as critical benchmarks of societal advancement and are key drivers of technological innovation. While electronic computers currently dominate as the primary instruments for information processing, their underlying manufacturing technologies are approaching physical and practical limits. This has prompted the search for alternative computational models and tools to meet the demands of future advancements. Over recent decades, scientists have explored various fields to develop novel computational frameworks. These efforts have led to the emergence of groundbreaking paradigms, such as artificial neural networks inspired by brain-like information processing, evolutionary computing based on genetic mechanisms, biocomputing utilizing the unique properties of biomolecules, quantum computing exploiting quantum phenomena, and optical computing leveraging the properties of light. Designed as an essential resource for readers interested in the principles and applications of biocomputing, this book establishes a foundational understanding of the subject while serving as a bridge to more advanced theoretical and practical exploration. A basic knowledge of molecular biology is recommended for readers to engage with the material fully. The translation was done using artificial intelligence. Subsequently, a human revision was done primarily in terms of content. |
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