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020 _a9789819733859
_9978-981-97-3385-9
024 7 _a10.1007/978-981-97-3385-9
_2doi
050 4 _aQA76.7-.73
072 7 _aUMX
_2bicssc
072 7 _aCOM051010
_2bisacsh
072 7 _aUMX
_2thema
100 1 _aOkoye, Kingsley.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980203
245 1 0 _aR Programming
_h[electronic resource] :
_bStatistical Data Analysis in Research /
_cby Kingsley Okoye, Samira Hosseini.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXV, 309 p. 361 illus., 210 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction 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 _aThis 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 _aProgramming languages (Electronic computers).
_966206
650 0 _aMathematical statistics.
_967233
650 0 _aMathematical statistics
_xData processing.
_964750
650 0 _aComputer science
_xMathematics.
_964041
650 0 _aInformation technology
_xManagement.
_957223
650 1 4 _aProgramming Language.
_966208
650 2 4 _aMathematical Statistics.
_967233
650 2 4 _aStatistics and Computing.
_966446
650 2 4 _aMathematical Applications in Computer Science.
_965518
650 2 4 _aComputer Application in Administrative Data Processing.
_966531
700 1 _aHosseini, Samira.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980204
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819733842
776 0 8 _iPrinted edition:
_z9789819733866
776 0 8 _iPrinted edition:
_z9789819733873
856 4 0 _uhttps://doi.org/10.1007/978-981-97-3385-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
999 _c61431
_d61431