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Record Nr. |
UNISA996309110703316 |
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Autore |
Scherstjanoi Elke |
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Titolo |
Zwei Staaten, zwei Literaturen? : Das internationale Kolloquium des Schriftstellerverbandes in der DDR, Dezember 1964. Eine Dokumentation / / Elke Scherstjanoi |
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Pubbl/distr/stampa |
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De Gruyter, 2008 |
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Berlin ; ; Boston : , : Oldenbourg Wissenschaftsverlag, , [2010] |
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©2008 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (206 p.) |
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Collana |
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Schriftenreihe der Vierteljahrshefte für Zeitgeschichte ; ; 96 |
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Classificazione |
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Disciplina |
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Soggetti |
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German literature - Germany (East) - History and criticism |
German literature - Germany (West) - History and criticism |
German literature - 20th century - History and criticism |
Germany (East) Intellectual life Congresses |
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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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Description based upon print version of record. |
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Nota di contenuto |
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Front Matter -- Protokoll der Arbeitsbesprechung im Sekretariat des Deutschen Schriftstellerverbandes am 13. Oktober 1964 (Auszug) -- Bericht des Sekretariats des Deutschen Schriftstellerverbandes, Dezember 1964 -- Diskussionsteilnehmer aus der DDR -- Back Matter |
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Sommario/riassunto |
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Anfang der 1960er Jahre erlebte die Kulturszene der DDR eine kurze Periode des Tauwetters. Eine Folge war die offene Diskussion über die "Existenz zweier deutscher Staaten und die Lage in der Literatur", die prominente Schriftsteller und Kulturfunktionäre der Ostblockländer vom 1. bis 5. Dezember 1964 in Berlin führten. Das Treffen nahm einen überraschenden Verlauf. Einige ausländische Gäste sprachen unverhohlen von anhaltendem Dogmatismus in der ostdeutschen Kulturpolitik. Und auch unter den DDR-Literaten gingen die Meinungen über die ästhetischen Mittel und politischen Aufgaben künstlerischen Schaffens in Ost und West auseinander, was Teile der SED-Führung wieder eine stärkere Lenkung der Literatur fordern ließ. Das Protokoll des Kolloquiums, das hier erstmals veröffentlicht wird, ist ein höchst anschauliches Zeugnis der kulturellen und politischen Entwicklung in |
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der DDR zwischen dem Mauerbau im August 1961 und dem kulturpolitischen Kahlschlag von Ende 1965. |
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2. |
Record Nr. |
UNINA9910300650103321 |
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Autore |
Wiley Joshua |
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Titolo |
Beginning R : an introduction to statistical programming / / Dr. Joshua F. Wiley, Larry A. Pace |
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Pubbl/distr/stampa |
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Berkeley, CA : , : Apress, , [2015] |
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©2015 |
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ISBN |
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Edizione |
[Second edition] |
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Descrizione fisica |
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1 online resource (337 pages) : illustrations |
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Collana |
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The expert's voice in programming |
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Disciplina |
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Soggetti |
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Programming languages (Electronic computers) |
Computer software |
R (Computer program language) |
R (Llenguatge de programació) |
Programming Languages, Compilers, Interpreters |
Mathematical Software |
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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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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Contents at a Glance; Contents; About the Author; In Memoriam; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Getting Star ted; 1.1 What is R, Anyway?; 1.2 A First R Session; 1.3 Your Second R Session; 1.3.1 Working with Indexes; 1.3.2 Representing Missing Data in R; 1.3.3 Vectors and Vectorization in R; 1.3.4 A Brief Introduction to Matrices; 1.3.5 More on Lists; 1.3.6 A Quick Introduction to Data Frames; Chapter 2: Dealing with Dates, Strings, and Data Frames; 2.1 Working with Dates and Times; 2.2 Working with Strings |
Chapter 5: Functional Programming 5.1 Scoping Rules; 5.2 Reserved Names and Syntactically Correct Names; 5.3 Functions and Arguments; 5.4 Some Example Functions; 5.4.1 Guess the Number; 5.4.2 A |
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Function with Arguments; 5.5 Classes and Methods; 5.5.1 S3 Class and Method Example; 5.5.2 S3 Methods for Existing Classes; Chapter 6: Probability Distributions; 6.1 Discrete Probability Distributions; 6.2 The Binomial Distribution; 6.2.1 The Poisson Distribution; 6.2.2 Some Other Discrete Distributions; 6.3 Continuous Probability Distributions; 6.3.1 The Normal Distribution |
6.3.2 The t Distribution 6.3.3 The F distribution; 6.3.4 The Chi-Square Distribution; References; Chapter 7: Working with Tables; 7.1 Working with One-Way Tables; 7.2 Working with Two-Way Tables; Chapter 8: Descriptive Statistics and Exploratory Data Analysis; 8.1 Central Tendency ; 8.1.1 The Mean; 8.1.2 The Median; 8.1.3 The Mode; 8.2 Variability ; 8.2.1 The Range; 8.2.2 The Variance and Standard Deviation ; 8.3 Boxplots and Stem-and-Leaf Displays ; 8.4 Using the fBasics Package for Summary Statistics; References; Chapter 9: Working with Graphics |
9.1 Creating Effective Graphics 9.2 Graphing Nominal and Ordinal Data; 9.3 Graphing Scale Data; 9.3.1 Boxplots Revisited ; 9.3.2 Histograms and Dotplots; 9.3.3 Frequency Polygons and Smoothed Density Plots; 9.3.4 Graphing Bivariate Data; References; Chapter 10: Traditional Statistical Methods; 10.1 Estimation and Confidence Intervals; 10.1.1 Confidence Intervals for Means; 10.1.2 Confidence Intervals for Proportions; 10.1.3 Confidence Intervals for the Variance; 10.2 Hypothesis Tests with One Sample; 10.3 Hypothesis Tests with Two Samples; References |
Chapter 11: Modern Statistical Methods |
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Sommario/riassunto |
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Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3. R is a powerful open-source language and programming environment for statistics and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for data analysis and research. What You Will Learn: How to acquire and install R Hot to import and export data and scripts How to analyze data and generate graphics How to program in R to write custom functions Hot to use R for interactive statistical explorations How to conduct bootstrapping and other advanced techniques. |
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