R Programming (Record no. 88514)

000 -LEADER
fixed length control field 05678nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-981-97-3385-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730172728.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240708s2024 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789819733859
-- 978-981-97-3385-9
082 04 - CLASSIFICATION NUMBER
Call Number 005.13
100 1# - AUTHOR NAME
Author Okoye, Kingsley.
245 10 - TITLE STATEMENT
Title R Programming
Sub Title Statistical Data Analysis in Research /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XV, 309 p. 361 illus., 210 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction to R programming and RStudio Integrated Development Environment (IDE) -- Working with Data in R: Objects, Vectors, Factors, Packages and Libraries, and Data Visualization -- Test of Normality and Reliability of Data in R -- Choosing between Parametric and Non-Parametric Tests in Statistical Data Analysis -- Understanding Dependent and Independent Variables in Research Experiments and Hypothesis Testing -- Understanding the Different Types of Statistical Data Analysis and Methods -- Regression Analysis in R: Linear and Logistic Regression -- T-test Statistics in R: Independent samples, Paired sample, and One sample ttests -- Analysis of Variance (ANOVA) in R: One-way and Two-way ANOVA -- Chi-squared (X2) Statistical Test in R -- Mann Whitney U test and Kruskal Wallis H test Statistics in R -- Correlation Tests in R: Pearson cor, Kendall's tau, and Spearman's rho -- Wilcoxon Statistics in R: Signed-Rank test and Rank-Sum test.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Mathematics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Management.
700 1# - AUTHOR 2
Author 2 Hosseini, Samira.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-97-3385-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2024.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Programming languages (Electronic computers).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical statistics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical statistics
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-- Computer science
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-- Information technology
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Programming Language.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Statistics.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics and Computing.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Applications in Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Application in Administrative Data Processing.
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No items available.