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Journal articles on the topic 'R statistical software'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Irie, Go, and Takashi Satou. "R; a statistical analysis software." Journal of The Institute of Image Information and Television Engineers 63, no. 11 (2010): 1540–43. http://dx.doi.org/10.3169/itej.63.1540.

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Hanum, Herlina. "PELATIHAN SOFTWARE R UNTUK ANALISIS STATISTIK1." Jurnal Pengabdian Sriwijaya 7, no. 2 (2019): 754–59. http://dx.doi.org/10.37061/jps.v7i2.9756.

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R is a very useful software in statistical analysis. Its open-source nature makes it easy for users to download and use it freely. Its relatively small size allows R to be installed and used on a laptop because it doesn't use much laptop memory. Users are also facilitated to learn statistical analysis using R because there are many learning resources available which are also easily accessible. But the existence and ease of this has not been widely known by users of statistical analysis. To further introduce R to the public using statistical analysis, R training was conducted through the commun

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Lorenz, Akiva J., Barry S. Markman, and Shlomo Sawilowsky. "Caution for Software Use of New Statistical Methods (R)." Journal of Modern Applied Statistical Methods 14, no. 2 (2015): 275–81. http://dx.doi.org/10.22237/jmasm/1446351540.

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Filzmoser, Peter, Cristian Gatu, and Achim Zeileis. "Special issue on statistical algorithms and software in R." Computational Statistics & Data Analysis 71 (March 2014): 887–88. http://dx.doi.org/10.1016/j.csda.2013.10.012.

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Zhukovska, Victoriia V., Oleksandr O. Mosiiuk та Veronika V. Komarenko. "ЗАСТОСУВАННЯ ПРОГРАМНОГО ПАКЕТУ R У НАУКОВИХ ДОСЛІДЖЕННЯХ МАЙБУТНІХ ФІЛОЛОГІВ". Information Technologies and Learning Tools 66, № 4 (2018): 272. http://dx.doi.org/10.33407/itlt.v66i4.2196.

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Corpus linguistics is a newly emerging field of study in applied linguistics that deals with construction, processing, and exploitation of text corpora. To date, a high-quality analysis of vast amounts of empirical language data provided by computerized corpora is impossible without computer technologies and relevant statistical methods. Therefore, teaching future philologists to effectively apply statistical computer programs is an important stage in their research training. The article discusses the possibilities of using one of the leading in Western linguistics, but not well-known in Ukrai

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DOS SANTOS FERREIRA, ROBSON, VERÔNICA YUMI KATAOKA, and MONICA KARRER. "TEACHING PROBABILITY WITH THE SUPPORT OF THE R STATISTICAL SOFTWARE." STATISTICS EDUCATION RESEARCH JOURNAL 13, no. 2 (2014): 132–47. http://dx.doi.org/10.52041/serj.v13i2.286.

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The objective of this paper is to discuss aspects of high school students’ learning of probability in a context where they are supported by the statistical software R. We report on the application of a teaching experiment, constructed using the perspective of Gal’s probabilistic literacy and Papert’s constructionism. The results show improvement in students’ learning of basic concepts, such as: random experiment, estimation of probabilities, and calculation of probabilities using a tree diagram. The use of R allowed students to extend their reasoning beyond that developed from paper-and-pencil

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Templ, Matthias, and Valentin Todorov. "The Software Environment R for Official Statistics and Survey Methodology." Austrian Journal of Statistics 45, no. 1 (2016): 97–124. http://dx.doi.org/10.17713/ajs.v45i1.100.

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The open-source programming language and software environment R is currently one of the most widely used and popular software tools for statistics and data analysis. This contribution provides an overview of important R packages used in official statistics and survey methodology and discusses the usefulness of R in the daily work of a statistical office. Examples of activities and developments in R related projects in several national and international statistical offices are given. The focus is not only on the internal infrastructure that national and international statistical offices provide

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Rode, Jacob B., and Megan M. Ringel. "Statistical Software Output in the Classroom: A Comparison of R and SPSS." Teaching of Psychology 46, no. 4 (2019): 319–27. http://dx.doi.org/10.1177/0098628319872605.

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The current study examines whether R or SPSS output induces greater initial anxiety in students and whether anxiety toward one or both changes after being taught one type of software output throughout the course. The authors each taught an introductory statistics course, with the first course ( n = 43) teaching R output exclusively and the second course ( n = 39) teaching SPSS output exclusively. Students in both courses were given surveys assessing their anxiety and confidence toward R and SPSS output on the first and last days of class. Students initially reported greater anxiety and lower c

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Růžička, Jan. "Integrating DROOLS and R software for intelligent map system." Geoinformatics FCE CTU 7 (December 29, 2011): 85–92. http://dx.doi.org/10.14311/gi.7.7.

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The paper describes intelligent map system that allows to check errors in map sheets or to help with a map sheet creation. The system is based on expert system DROOLS, ontology created in Protége and statistical software R. Prototype of the system should evaluate that this kind of integration is possible, so the system is not full of rules. The prototype is filled with twenty rules written in DRL language and with more than thirty items from the ontology. The paper should show how all of these components can be integrated together to allow such kind of a map sheet evaluation. The system is now

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Lockstone, H. E. "Exon array data analysis using Affymetrix power tools and R statistical software." Briefings in Bioinformatics 12, no. 6 (2011): 634–44. http://dx.doi.org/10.1093/bib/bbq086.

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Haghish, E. F. "Seamless interactive language interfacing between R and Stata." Stata Journal: Promoting communications on statistics and Stata 19, no. 1 (2019): 61–82. http://dx.doi.org/10.1177/1536867x19830891.

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In this article, I propose a new approach to language interfacing for statistical software by allowing automatic interprocess communication between R and Stata. I advocate interactive language interfacing in statistical software by automatizing data communication. I introduce the rcall package and provide examples of how the R language can be used interactively within Stata or embedded into Stata programs using the proposed approach to interfacing. Moreover, I discuss the pros and cons of object synchronization in language interfacing.

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Bivand, Roger, Giovanni Millo, and Gianfranco Piras. "A Review of Software for Spatial Econometrics in R." Mathematics 9, no. 11 (2021): 1276. http://dx.doi.org/10.3390/math9111276.

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The software for spatial econometrics available in the R system for statistical computing is reviewed. The methods are illustrated in a historical perspective, highlighting the main lines of development and employing historically relevant datasets in the examples. Estimators and tests for spatial cross-sectional and panel models based either on maximum likelihood or on generalized moments methods are presented. The paper is concluded reviewing some current active lines of research in spatial econometric software methods.

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Haaf, Robert, Brent Duncan, Elizabeth Skarakis-Doyle, Maria Carew, and Paula Kapitan. "Computer-Based Language Assessment Software." Language, Speech, and Hearing Services in Schools 30, no. 1 (1999): 68–74. http://dx.doi.org/10.1044/0161-1461.3001.68.

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Nonstandard presentation and response formats are often employed by speech-language pathologists when clients are unable to perform the pointing response required of many standardized tests. However, any adaptation to test administration potentially compromises the norming standards of that test. The present study investigated the effects of computerized presentation of the Peabody Picture Vocabulary Test-Revised (PPVT-R, Dunn & Dunn, 1981) Form M, using two computer-based response formats. Seventy-two normally developing children between the ages of 4:0 (years:months) and 8:11 participate

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Peternelli, Luiz Alexandre. "Program R: applications in plant breeding." Crop Breeding and Applied Biotechnology 11, spe (2011): 91–92. http://dx.doi.org/10.1590/s1984-70332011000500014.

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Nowadays the demand for so-called free, or open source software for data analysis as well as the appeal to use it is great. An public domain software that has become extremely well-known, with ever-increasing numbers of fans and even co-workers, is Environment R, or simply R. R is extremely useful for data analysis and manipulation in view of a range of tools already implemented. Also, R is not simply a statistical program, because, by its easy on using internal functions and also creating new ones, statistical procedures applied to data can also be created, manipulated, evaluated and interpre

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Wan, Ying-Wooi, Genevera I. Allen, and Zhandong Liu. "TCGA2STAT: simple TCGA data access for integrated statistical analysis in R." Bioinformatics 32, no. 6 (2015): 952–54. http://dx.doi.org/10.1093/bioinformatics/btv677.

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Abstract Motivation: Massive amounts of high-throughput genomics data profiled from tumor samples were made publicly available by the Cancer Genome Atlas (TCGA). Results: We have developed an open source software package, TCGA2STAT, to obtain the TCGA data, wrangle it, and pre-process it into a format ready for multivariate and integrated statistical analysis in the R environment. In a user-friendly format with one single function call, our package downloads and fully processes the desired TCGA data to be seamlessly integrated into a computational analysis pipeline. No further technical or bio

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Silva, Laércio Junio da, André Dantas de Medeiros, and Ariadne Morbeck Santos Oliveira. "SeedCalc, a new automated R software tool for germination and seedling length data processing." Journal of Seed Science 41, no. 2 (2019): 250–57. http://dx.doi.org/10.1590/2317-1545v42n2217267.

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Abstract: The need to optimize seed quality assessment using new, more accessible, and modern computational resources has led to the emergence of new tools. In this paper, we introduce SeedCalc, a new R software package developed to process germination and seedling length data. The functions included in SeedCalc allow fast and efficient data processing, offering greater reliability to the variables generated and facilitating statistical analysis itself since the data are already processed with the appropriate structure to be statistically analyzed in the R software. SeedCalc is available free

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Ildiko, Mártha Krisztina, Pálffy Balázs Ákos, and Panaite Irinel. "Radiographic Comparison of Vertical Skeletal and Dental Parameters in Skeletal Open Bite." Acta Medica Marisiensis 62, no. 3 (2016): 330–33. http://dx.doi.org/10.1515/amma-2016-0034.

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AbstractObjective: The purpose of our randomized study was to compare the skeletal and dental values in open bite cases using lateral cephalometric analysis and panoramic X-rays analysis and to evaluate if PR is a reliable diagnostic method in skeletal malocclusions.Methods: 21 (6 boys, 15 girls) patient with skeletal open bite were selected and both radiological examinations were performed. “Modified cephalometric analysis” on panoramic X-rays and Steiner’s cephalometric analysis was performed using AudaxCeph software. Statistical analysis was performed using the Pearson correlation method an

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Kim, Yeongsic, Hae-il Park, Hae Kyung Lee, et al. "Development of Statistical Software for the Korean Laboratory Accreditation Program Using R Language: LaboStats." Annals of Laboratory Medicine 39, no. 6 (2019): 552–60. http://dx.doi.org/10.3343/alm.2019.39.6.552.

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Iacobucci, Alessandra, and Christian Robert. "The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff." CHANCE 25, no. 2 (2012): 55–56. http://dx.doi.org/10.1080/09332480.2012.685374.

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Welty, Leah J., Luke V. Rasmussen, Abigail S. Baldridge, and Eric W. Whitley. "Facilitating reproducible research through direct connection of data analysis with manuscript preparation: StatTag for connecting statistical software to Microsoft Word." JAMIA Open 3, no. 3 (2020): 342–58. http://dx.doi.org/10.1093/jamiaopen/ooaa043.

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Abstract Objectives To enhance reproducible research by creating a broadly accessible, free, open-source software tool for connecting Microsoft Word to statistical programs (R/R Markdown, Python, SAS, Stata) so that results may be automatically updated in a manuscript. Materials and Methods We developed StatTag for Windows as a Microsoft Word plug-in using C# and for macOS as a native application using Objective-C. Source code is available under the MIT license at https://github.com/stattag. Results StatTag links analysis file(s) (R/R Markdown, SAS, Stata, or Python) and a Word document, invok

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Ishida, Akio, Ukyo Aibara, Jun Murakami, et al. "Analysis of Rehabilitation Data by Multi-Dimensional Principal Component Analysis Method Using the Statistical Software R." Advanced Materials Research 823 (October 2013): 650–56. http://dx.doi.org/10.4028/www.scientific.net/amr.823.650.

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The multi-dimensional principal component analysis (MPCA), which is an extension of the well-known principal component analysis (PCA), is proposed to reduce the dimension and to extract the feature of the multi-dimensional data. We have analyzed the rehabilitation data, which is known as the Functional Independence Measure (FIM), routinely measured from inpatients of a hospital by using MPCA. This time, we implemented the MPCA program by the statistical software R, and carried out the analysis of that data with changed configuration from the previous works in the environment of the R statistic

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ION (MANU), Mădălina Viorica, and Ilie VASILE. "CONTEMPORARY DATA SCIENCE FOR FINANCE STUDENTS. ESSENTIAL FEATURES OF COMMONLY USED STATISTICAL SOFTWARE - A COMPARATIVE STUDY." Business Excellence and Management 9, no. 2 (2019): 14–20. http://dx.doi.org/10.24818/beman/2019.9.2-02.

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This paper inventories some of the essential traits of the software preferred by researchers, students and professors, such as R or RStudio, or Matlab and also their possible utilizations. In order to fill the gap in the Romanian literature and help finance students in choosing proper tools according to the research purpose, this comparative study aims at bringing a fresh, useful perspective in the relevant literature. In Romania, the use of R was the focus of several international conferences on official statistics held in Bucharest, and others having business excellence, innovation and susta

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Jensen, Signe M., Felix M. Kluxen, Jens C. Streibig, Nina Cedergreen, and Christian Ritz. "bmd: an R package for benchmark dose estimation." PeerJ 8 (December 17, 2020): e10557. http://dx.doi.org/10.7717/peerj.10557.

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The benchmark dose (BMD) methodology is used to derive a hazard characterization measure for risk assessment in toxicology or ecotoxicology. The present paper’s objective is to introduce the R extension package bmd, which facilitates the estimation of BMD and the benchmark dose lower limit for a wide range of dose-response models via the popular package drc. It allows using the most current statistical methods for BMD estimation, including model averaging. The package bmd can be used for BMD estimation for binomial, continuous, and count data in a simple set up or from complex hierarchical des

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Ding, Hongyu. "An Analysis of Domestic Tourism Consumption Based on R Software." MATEC Web of Conferences 228 (2018): 05006. http://dx.doi.org/10.1051/matecconf/201822805006.

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R is a software system which can be used for data processing, calculation and mapping. The syntax of this language is superficially similar to C, but semantically it is functional programming language. It is widely used in statistical analysis. So this paper used it to analyze China domestic tourism consumption data during 1999-2015, and analyzed the main factors affecting the consumption level of domestic tourism in China from residents’ disposable income, GDP, per capita consumption of tourists, tourists, the mileage of railways and the number of travel agencies. Finally it established and s

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Hu, LP. "Statistical analysis using SAS software package for data of R×C contingency table (Part two)." Journal of Chinese Integrative Medicine 7, no. 9 (2009): 878–82. http://dx.doi.org/10.3736/jcim20090915.

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Viorica Manu, Madalina, and Ilie Vasile. "Contemporary Data Science for Finance Students: A Comparative Study of Essential Features of Commonly Used Statistical Software." International Journal of Innovation and Economic Development 6, no. 2 (2020): 19–24. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.62.2002.

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In this paper, we compare some of the essential traits of the software preferred by researchers, students, and professors, such as R or RStudio, or Matlab. In order to fill the gap in the Romanian literature and help finance students in choosing proper tools according to the research purpose, this comparative study aims at bringing a fresh, useful perspective in the relevant literature. In Romania, the use of R was the focus of several international conferences on official statistics held in Bucharest, and others having business excellence, innovation, and sustainability as purpose, while Evie

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Azevedo, Camila Ferreira, Moysés Nascimento, Vitor Cunha Fontes, Fabyano Fonseca e. Silva, Marcos Deon Vilela de Resende, and Cosme Damião Cruz. "GenomicLand: Software for genome-wide association studies and genomic prediction." Acta Scientiarum. Agronomy 41, no. 1 (2019): 45361. http://dx.doi.org/10.4025/actasciagron.v41i1.45361.

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GenomicLand is free software intended for prediction and genomic association studies based on the R software. This computational tool has an intuitive interface and supports large genomic databases, without requiring the user to use the command line. GenomicLand is available in English, can be downloaded from the Internet (https://licaeufv.wordpress.com/), and requires the Windows or Linux operating system. The software includes statistical procedures based on mixed models, Bayesian inference, dimensionality reduction and artificial intelligence. Examples of data files that can be processed by

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Niu, Gao, Richard S. Segall, Zichen Zhao, and Zhijian Wu. "A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities." International Journal of Open Source Software and Processes 12, no. 1 (2021): 1–20. http://dx.doi.org/10.4018/ijossp.2021010101.

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This paper discusses the definitions of open source software, free software and freeware, and the concept of big data. The authors then introduce R and Python as the two most popular open source statistical software (OSSS). Additional OSSS, such as JASP, PSPP, GRETL, SOFA Statistics, Octave, KNIME, and Scilab, are also introduced in this paper with function descriptions and modeling examples. They further discuss OSSS's capability in artificial intelligence application and modeling and Popular OSSS-based machine learning libraries and systems. The paper intends to provide a reference for reade

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Slezák, Peter, Pavol Bokes, Pavol Námer, and Iveta Waczulíková. "Microsoft Excel add-in for the statistical analysis of contingency tables." International Journal for Innovation Education and Research 2, no. 5 (2014): 90–100. http://dx.doi.org/10.31686/ijier.vol2.iss5.188.

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This paper introduces “Contingency table analysis”, a freely available menu-driven add-in program for Microsoft EXCEL, written in Visual Basic for Applications (VBA), for basic univariate and bivariate statistical analyses of contingency tables. The program provides modules for the statistical analysis of proportions, 2 × 2 tables, stratified 2 × 2 tables, and R × C tables. We compare the results of the analyses performed using our software with those obtained by commercially available statistical software. The comparison shows that our software performs equally well. The use of the add-in fac

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STEMOCK, BRYSON, and LUCY KERNS. "USE OF COMMERCIAL AND FREE SOFTWARE FOR TEACHING STATISTICS." STATISTICS EDUCATION RESEARCH JOURNAL 18, no. 2 (2019): 54–67. http://dx.doi.org/10.52041/serj.v18i2.140.

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This study investigates the effectiveness of two statistical software packages, the commercial software, SPSS, and the free software, R Version 3.5.0, in teaching statistics, by comparing grades earned by students in an introductory statistics course. Students taught using R earned slightly higher grades overall than those in the SPSS class, although the difference between the two groups of students was found to be not significantly different. The responses given by students on the end of semester survey for the use of technology indicated that students felt comfortable with both software pack

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Rahn, Karl-Heinz, Steffen Klatt, Edwin Haas, and Klaus Butterbach-Bahl. "Improving efficiency of a statistical analysis of complex ecological models, when using the statistical software R by parallelising tasks with Rmpi." Ecological Informatics 15 (May 2013): 53–57. http://dx.doi.org/10.1016/j.ecoinf.2013.02.005.

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Khadim, Inaam H., and Khalid Hussain Hatif. "Statistical Treatment of the Gamma-Ray Spectrum Using the Language Programming R." NeuroQuantology 19, no. 2 (2021): 50–60. http://dx.doi.org/10.14704/nq.2021.19.2.nq21017.

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In this work we use the laws of statistics and statistical distributions software to try to understand the random statistical nature of the dissolution of gamma rays and their interaction with the material by studying the spectrum regions of the sodium-22 spectrum using the statistical programming language R. such Normality test, Anova Test as well as Pearson correlation coefficient test and the linear Regression test and we were found that there is no strong statistical relationship between the random variables studied using linear regression, also it was found that the average mean of the st

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Wang, Pin, and Hai Ping Huang. "On the W&R and RSI Expert Systems of Securities Software." Applied Mechanics and Materials 433-435 (October 2013): 1685–88. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.1685.

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Using the method of statistical experiment and based on real and open data of securities, the research conducted a test to the W&R and RSI expert system of securities trading software. Taking annual net profit margin, rate of return, and win rate as the management objectives, the research compared and analyzed the two similar reversal trend indicators on the basis of mathematic statistics theories, and achieved results that the annual rate of return and net profit margin of the RSI expert system are superior to that of the W&R expert system for 4.72 times, and that the annual number of

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Pollard, Daniel A., Thomas D. Pollard, and Katherine S. Pollard. "Empowering statistical methods for cellular and molecular biologists." Molecular Biology of the Cell 30, no. 12 (2019): 1359–68. http://dx.doi.org/10.1091/mbc.e15-02-0076.

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We provide guidelines for using statistical methods to analyze the types of experiments reported in cellular and molecular biology journals such as Molecular Biology of the Cell. Our aim is to help experimentalists use these methods skillfully, avoid mistakes, and extract the maximum amount of information from their laboratory work. We focus on comparing the average values of control and experimental samples. A Supplemental Tutorial provides examples of how to analyze experimental data using R software.

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Tirta, Made, and Dian Anggraeni. "The Development of Web-based Graphical User Interface for Learning and Fitting Generalized Estimating Equation with Spline Smoothers." Jurnal ILMU DASAR 19, no. 1 (2018): 63. http://dx.doi.org/10.19184/jid.v19i1.6997.

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Statistical modeling (regression analyses) have been growing rapidly into various directions to accommodate various data conditions. For longitudinal or repeated measures data, one of the suitable models is GEE (Generalized Estimating Equation). In practice, to do complex modeling such as GEE, the use of statistical software is necessary and it is available on free open source software R. However, GEE modeling on R can only be access through command line interface (CLI), and most practical researchers very much rely on Graphical User Interface (GUI) based statistics software. To make access to

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Hu, LP. "Statistical analysis using SAS software package for data of 2×C and R×2 contingency tables." Journal of Chinese Integrative Medicine 7, no. 10 (2009): 991. http://dx.doi.org/10.3736/jcim20091014.

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Flores, Miguel, Rubén Fernández-Casal, Salvador Naya, Javier Tarrío-Saavedra, and Roberto Bossano. "ILS: An R package for statistical analysis in Interlaboratory Studies." Chemometrics and Intelligent Laboratory Systems 181 (October 2018): 11–20. http://dx.doi.org/10.1016/j.chemolab.2018.07.013.

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Baniya, Chitra B. "Data Analysis Tools: Essential for Scientific Community." ZOO-Journal 5 (December 31, 2019): 23–26. http://dx.doi.org/10.3126/zooj.v5i0.34778.

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Data analysis tools and software have been increasing each day in the academic field. They were classified into two categories: one category of statistical tool that needs money to buy its licence to use and install into owns computer. Such software are called closed software. Another category of tool or software is called open source tool or open software. This later group comes freely and one can get licence freely. Academicians are free to choose one. Definitely 'R' and its associated tools which we can download freely and use freely has no better alternatives. 'R' users have been increasin

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Gavrilovskaya, N. V. "LEARNING APP FOR FREE DEVELOPMENT RSTUDIO." Vestnik scientific and methodological council in environmental engineering and water management, no. 19 (2020): 35–39. http://dx.doi.org/10.26897/2618-8732-2020-35-39.

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The article stipulates the relevance of developing a training application for a free software development environment RStudio focused on the study of statistical methods for processing experimental data. A brief description of the high-level object-oriented programming language and environment for statistical calcula-tions and visualization of the initial and calculated data R is given; substantiates its effectiveness in the educa-tional process. The functionality of the developed software product is described.

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Stoenoiu, Carmen Elena. "Patterns in enterprise management software." Balkan Region Conference on Engineering and Business Education 2, no. 1 (2017): 292–300. http://dx.doi.org/10.1515/cplbu-2017-0038.

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Abstract In this paper a study was conducted on the complex integrated software that exists on the Romanian market. This consisted in identifying and analysing the size of the enterprise, the number of users, the technical characteristics determined by the type and number of modules included in the software and other information related to the implementation, according to the supplier's specifications. The primary analysis made it possible to obtain results regarding the integrated software market in Romania in terms of customer size, field of activity, software products that include the bigge

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Sungkono, Joko, and Kriswianti Nugrahaningsih. "PEMBELAJARAN TEORI PROBABILITAS MENGGUNAKAN R." Absis: Mathematics Education Journal 2, no. 1 (2021): 1. http://dx.doi.org/10.32585/absis.v2i1.858.

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In learning probability theory, if a series of statistical experiments is carried out several times, identifying the possible samples produced is not an easy thing. If this happens, then a significant probability problem will arise. The objective of this study is how to learn probability theory using R software. Based on the simulation results it can be concluded that by combining the syntax in R can be used to solve probability problems such as identifying sample points from experiments, events, event operations, probabilities and conditional probabilities. This will help students learning in

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Sen, Sedat, and Ragip Terzi. "A Comparison of Software Packages Available for DINA Model Estimation." Applied Psychological Measurement 44, no. 2 (2019): 150–64. http://dx.doi.org/10.1177/0146621619843822.

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This article provides a review of software packages for fitting maximum likelihood estimation of the deterministic input, noisy “and” gate (DINA) model. Six software packages—flexMIRT, Latent GOLD, mdltm, Mplus, OxEdit, and R—are considered. Each package is reviewed regarding data manipulation, statistical capabilities, output, and documentation. The results of these packages are compared using a sample data set and a Q-matrix. The article aims to give the reader a summary of the different capabilities of each package.

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Jiang, Zhehan. "Using the Linear Mixed-Effect Model Framework to Estimate Generalizability Variance Components in R." Methodology 14, no. 3 (2018): 133–42. http://dx.doi.org/10.1027/1614-2241/a000149.

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Abstract. Extending from classical test theory, G theory allows more sources of variations to be investigated and therefore provides the accuracy of generalizing observed scores to a broader universe. However, G theory has been used less due to the absence of analytic facilities for this purpose in popular statistical software packages. Besides, there is rarely a systematic G theory introduction in the linear mixed-effect model context, which is a widely taught technique in statistical analysis curricula. The present paper fits G theory into linear mixed-effect models and estimates the varianc

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Casas, Pau Fonseca i., and Raül Tormos. "Using the R Language to Manage and Show Statistical Information in the Cloud." Technologies 6, no. 4 (2018): 113. http://dx.doi.org/10.3390/technologies6040113.

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We present a methodology to enable users to interact with the statistical information (survey data) of a public opinion institute which is stored in Cloud infrastructure. Mainly using R, this approach was developed following the open-data philosophy. Also, as we used R, the implementation is mainly based on open-source software. R has several advantages from the point of view of data management and acquisition, as it is becoming a common framework that can be used to structure the processes involved in any statistical operation. It further simplifies the access to data and enables the use of a

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Malaj, Visar, and Arben Malaj. "Long Memory Volatility Models in R: Application to a Regional Blue Chips Index." European Journal of Interdisciplinary Studies 1, no. 2 (2015): 170. http://dx.doi.org/10.26417/ejis.v1i2.p170-179.

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An increasing number of researchers and analysts have formulated in the last decade innovative statistical equations for modelling and forecasting the volatility of financial returns. The evolution of technology and new software development have contributed positively to emerging economies, as well as in the improvement of market competition. We investigate in this study some experimental extensions of the multiplicative error model, which has been introduced by Engle (2002) for positive valued processes and it is specified as the product of a conditionally autoregressive scale factor and an i

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Malaj, Visar, and Arben Malaj. "Long Memory Volatility Models in R: Application to a Regional Blue Chips Index." European Journal of Interdisciplinary Studies 2, no. 1 (2015): 170. http://dx.doi.org/10.26417/ejis.v2i1.p170-179.

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An increasing number of researchers and analysts have formulated in the last decade innovative statistical equations for modelling and forecasting the volatility of financial returns. The evolution of technology and new software development have contributed positively to emerging economies, as well as in the improvement of market competition. We investigate in this study some experimental extensions of the multiplicative error model, which has been introduced by Engle (2002) for positive valued processes and it is specified as the product of a conditionally autoregressive scale factor and an i

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Parsons, Nick R., Matthew L. Costa, Juul Achten, and Nigel Stallard. "Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R." Computational Statistics & Data Analysis 53, no. 3 (2009): 632–41. http://dx.doi.org/10.1016/j.csda.2008.08.004.

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Neet, Matthew J., R. Heath Kelsey, Dwayne E. Porter, Dan W. Ramage, and Adrian B. Jones. "Model Results and Software Comparisons in Myrtle Beach, SC Using Virtual Beach and R Regression Toolboxes." Journal of South Carolina Water Resources, no. 2 (June 1, 2015): 80–85. http://dx.doi.org/10.34068/jscwr.02.09.

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Utilizing R software and a variety of data sources, daily forecasts of bacteria levels were developed and automated for beach waters in Myrtle Beach, SC. Modeled results are then shown for beach locations via a website and mobile device app. While R provides a robust set of tools for use in forecast modeling, the software has an extensive learning curve and requires skilled statistical interpretation of results. The Environmental Protection Agency (EPA) created the “Virtual Beach” software package to address these concerns. To evaluate the utility of the more user-friendly Virtual Beach modeli

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HUANG, YUANYUAN, STEPHEN BONETT, ANDRZEJ KLOCZKOWSKI, ROBERT JERNIGAN, and ZHIJUN WU. "P.R.E.S.S. — AN R-PACKAGE FOR EXPLORING RESIDUAL-LEVEL PROTEIN STRUCTURAL STATISTICS." Journal of Bioinformatics and Computational Biology 10, no. 03 (2012): 1242007. http://dx.doi.org/10.1142/s0219720012420073.

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P.R.E.S.S. is an R-package developed to allow researchers to get access to and manipulate a large set of statistical data on protein residue-level structural properties such as residue-level virtual bond lengths, virtual bond angles, and virtual torsion angles. A large set of high-resolution protein structures is downloaded and surveyed. Their residue-level structural properties are calculated and documented. The statistical distributions and correlations of these properties can be queried and displayed. Tools are also provided for modeling and analyzing a given structure in terms of its resid

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Gómez, Guadalupe, M. Luz Calle, Ramon Oller, and Klaus Langohr. "Tutorial on methods for interval-censored data and their implementation in R." Statistical Modelling 9, no. 4 (2009): 259–97. http://dx.doi.org/10.1177/1471082x0900900402.

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Interval censoring is encountered in many practical situations when the event of interest cannot be observed and it is only known to have occurred within a time window. The theory for the analysis of interval-censored data has been developed over the past three decades and several reviews have been written. However, it is still a common practice in medical and reliability studies to simplify the interval censoring structure of the data into a more standard right censoring situation by, for instance, imputing the midpoint of the censoring interval. The availability of software for right censori

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