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Grundlagen Der Mathematik F 1 4r Dummies

Author: Mark Zegarelli
Publisher: John Wiley & Sons
ISBN: 352769935X
Size: 10.79 MB
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Mathematik ist nicht jedermanns Sache und oft sind es gerade die Grundlagen, die fehlen: Wie berechnet man nochmal den Umfang eines Kreises? Wieviel Geld spare ich bei 30 % Rabatt? Und wie geht man Textaufgaben eigentlich richtig an? Fragen ï¿1⁄2ber Fragen - die Antworten finden Sie in diesem Buch. Egal ob Bruch- oder Prozentrechnung, Geometrie, Algebra, Wahrscheinlichkeitsrechnung oder Statistik, Mark Zegarelli erklï¿1⁄2rt es Ihnen einfach, mit Humor und immer schnell auf den Punkt. Frischen Sie Ihr Wissen auf, lernen Sie die Grundlagen der Mathematik und werden Sie ruckzuck zum Mathe-Ass.

An Introduction To Experimental Design And Statistics For Biology

Author: David Heath
Publisher: CRC Press
ISBN: 9780203499245
Size: 17.25 MB
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This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis. The author presents statistical concepts through common sense, non-mathematical explanations and diagrams. These are followed by the relevant formulae and illustrated by worked examples. The examples are drawn from all areas of biology, from biochemistry to ecology and from cell to animal biology. The book provides everything required in an introductory statistics course for biology undergraduates, and it is also useful for more specialized undergraduate courses in ecology, botany, and zoology.

Kompendium Systembiologie

Author: Andreas Kremling
Publisher: Springer-Verlag
ISBN: 3834886076
Size: 33.16 MB
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Das Buch beschreibt die Grundlagen der mathematischen Modellierung zellulärer Systeme. Nach einer Klassifikation von Modellen wird schwerpunktmäßig auf deterministische Modelle eingegangen und für alle relevanten zellulären Prozesse entsprechende Gleichungen angegeben. Anschließend werden eine Reihe von Verfahren zur Modellanalyse vorgestellt. Etwas kürzer werden Verfahren zum Reverse Engineering und zur Analyse von Netzwerkgraphen abgehandelt. Am Ende werden noch Verfahren der Parameteridentifikation besprochen.

Dna Methylation Microarrays

Author: Sun-Chong Wang
Publisher: CRC Press
ISBN: 9781420067286
Size: 77.10 MB
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Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays, many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics, the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis, the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor), public databases, and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming, this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis.

Introductory R A Beginner S Guide To Data Visualisation Statistical Analysis And Programming In R

Author: Robert Knell
Publisher: Robert Knell
ISBN: 0957597118
Size: 21.65 MB
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R is now the most widely used statistical software in academic science and it is rapidly expanding into other fields such as finance. R is almost limitlessly flexible and powerful, hence its appeal, but can be very difficult for the novice user. There are no easy pull-down menus, error messages are often cryptic and simple tasks like importing your data or exporting a graph can be difficult and frustrating. Introductory R is written for the novice user who knows a little about statistics but who hasn't yet got to grips with the ways of R. This new edition is completely revised and greatly expanded with new chapters on the basics of descriptive statistics and statistical testing, considerably more information on statistics and six new chapters on programming in R. Topics covered include: A walkthrough of the basics of R's command line interface Data structures including vectors, matrices and data frames R functions and how to use them Expanding your analysis and plotting capacities with add-in R packages A set of simple rules to follow to make sure you import your data properly An introduction to the script editor and advice on workflow A detailed introduction to drawing publication-standard graphs in R How to understand the help files and how to deal with some of the most common errors that you might encounter. Basic descriptive statistics The theory behind statistical testing and how to interpret the output of statistical tests Thorough coverage of the basics of data analysis in R with chapters on using chi-squared tests, t-tests, correlation analysis, regression, ANOVA and general linear models What the assumptions behind the analyses mean and how to test them using diagnostic plots Explanations of the summary tables produced for statistical analyses such as regression and ANOVA Writing your own functions in R Using table operations to manipulate matrices and data frames Using conditional statements and loops in R programmes. Writing longer R programmes. The techniques of statistical analysis in R are illustrated by a series of chapters where experimental and survey data are analysed. There is a strong emphasis on using real data from real scientific research, with all the problems and uncertainty that implies, rather than well-behaved made-up data that give ideal and easy to analyse results.

R In 10 Schritten

Author: Rainer Alexandrowicz
Publisher: UTB
ISBN: 3825284840
Size: 55.21 MB
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Programmierung mit R zum Selbststudium und als Begleitlektüre: Die freie Programmierumgebung R spielt eine zunehmend wichtige Rolle in den sozialwissenschaftlichen Studienrichtungen, allen voran der Psychologie. Das Buch führt in die Bedienung und Programmlogik von R ein. Neben dem nach didaktischen Gesichtspunkten gegliederten Aufbau erlaubt ein umfangreicher Index auch die Verwendung als Nachschlagewerk. Viele Querverweise ermöglichen zudem den Direkteinstieg bei einem bestimmten Thema. Das Buch ist für das Selbststudium geeignet und bietet sich als Begleitlektüre zu einer einführenden Statistikvorlesung an. Es werden keine besonderen PC-Kenntnisse vorausgesetzt. Statistikkenntnisse auf Bachelorniveau sind von Vorteil, können aber auch parallel zur Lektüre erworben werden. Vertiefende Textabschnitte, die beim ersten Lesen auch übersprungen werden können, sind gesondert gekennzeichnet.

Ecological Statistics

Author: Gordon A. Fox
Publisher: OUP Oxford
ISBN: 0191652881
Size: 65.48 MB
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The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

Biologie Von Parasiten

Author: Richard Lucius
Publisher: Springer-Verlag
ISBN: 3662548623
Size: 53.70 MB
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Die 3. vollständig überarbeitete Auflage dieses Buches führt in die Biologie parasitärer Einzeller, Würmer und Arthropoden ein. Die Autoren bieten auf Grundlage der aktuellen Systematik eine Übersicht über die verschiedenen Parasitengruppen. Ausführlich wird auf wichtige Infektionserreger, wie die der Malaria, Schlafkrankheit und Toxoplasmose eingegangen, wobei die molekularen Grundlagen der Pathogene erläutert werden. Außerdem werden Parasiten als Krankheitsüberträger dargestellt und wichtige Infektionskrankheiten, die bei Tieren vorkommen, besprochen. Daher wendet sich dieses Buch sowohl an Biologen, als auch an Veterinärmediziner und Mediziner. In den einzelnen Kapiteln kommen die Anpassungen an die parasitische Lebensweise zur Sprache. Anhand häufiger Vertreter werden exemplarisch typische Lebenszyklen, die Immunreaktionen und die resultierenden Krankheitsbilder erklärt. Viele Abbildungen veranschaulichen dabei den Text. Die Prüfungsfragen am Ende eines jeden Kapitels helfen den Lerninhalt zu rekapitulieren und zu verinnerlichen.

Experimental Design For Laboratory Biologists

Author: Stanley E. Lazic
Publisher: Cambridge University Press
ISBN: 1316810674
Size: 28.59 MB
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Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (https://stanlazic.github.io/EDLB.html) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry.