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Software for learning and for doing statistics and probability – Looking back and looking forward from a personal perspective Software para aprender y para hacer estadística y probabilidad – Mirando atrás y adelante desde una perspectiva personal Rolf Biehler Universität Paderborn, Germany Abstract The paper discusses requirements for software that supports both the learning and the doing of statistics. It looks back into the 1990s and looks forward to new challenges for such tools stemming from an updated conception of statistical literacy and challenges from big data, the exploding use of data in society and the emergence of data science. A focus is on Fathom, TinkerPlots and Codap, which are looked at from the perspective of requirements for tools for statistics education. Experiences and success conditions for using these tools in various educational contexts are reported, namely in primary and secondary education and pre- service and in-service teacher education. New challenges from data science require new tools for education with new features. The paper finishes with some ideas and experience from a recent project on data science education at the upper secondary level Keywords: software for learning and doing statistics, key attributes of software, data science education, statistical literacy Resumen El artículo discute los requisitos que el software debe cumplir para que pueda apoyar tanto el aprendizaje como la práctica de la estadística. Mira hacia la década de 1990 y hacia el futuro, para identificar los nuevos desafíos que para estas herramientas surgen de una concepción actualizada de la alfabetización estadística y los desafíos que plantean el uso de big data, la explosión del uso masivo de datos en la sociedad y la emergencia de la ciencia de los datos. -
Manual Eviews 6 Espanol Pdf
Manual Eviews 6 Espanol Pdf Statistical, forecasting, and modeling tools with a simple object-oriented interface. Corel VideoStudio Pro X8 User Guide PDF. 6. Corel VideoStudio Pro User Guide. EViews Illustrated.book Page 1 Thursday, March 19, 2015 9:53 AM Microsoft Corporation. All other product names mentioned in this manual may be Page 6. On this page you can download PDF book Onan Generator Shop Manual Model It can be done by copy-and-paste as well, which is described in EViews' help. This software product, including program code and manual, is copyrighted, and all rights manual or the EViews program. 6. Custom Edit Fields in EViews. 3 Achievements, 4 Performance, 5 Licensing and availability, 6 Software packages editing and embedding SageMath within LaTeX documents, The Python standard library, Archived from the original (PDF) on 2007-06-27. Català · Čeština · Deutsch · Español · Français · Bahasa Indonesia · Italiano · Nederlands. Manual Eviews 6 Espanol Pdf Read/Download Software Lga 775 Related Programs Free Download write Offline Spanish Pilz 4BB0D53E-1167- 4A61-8661-62FB02050D02 EViews 6 Why do I have 2. 0.4 sourceblog.sourceforge.net/maximo- 6-training-manual.pdf 2015-09-03.net/applied-advanced-econometrics-using-eviews.pdf 2015-08- 19 08:25:07 sourceblog.sourceforge.net/manual-de-primavera-p6-en-espanol.pdf. This software product, including program code and manual, is copyrighted, and all you may access the PDF files from within EViews by clicking on Help in the For discussion, see “Command and Capture Window Docking” on page 6. Software Installation for Eviews 8 for SMU Student - Free download as PDF File (.pdf), Text file (.txt) or read online for free. -
Antibiotic De-Escalation Experience in the Setting of Emergency Department: a Retrospective, Observational Study
Journal of Clinical Medicine Article Antibiotic De-escalation Experience in the Setting of Emergency Department: A Retrospective, Observational Study Silvia Corcione 1,2, Simone Mornese Pinna 1 , Tommaso Lupia 3,* , Alice Trentalange 1, Erika Germanò 1, Rossana Cavallo 4, Enrico Lupia 1 and Francesco Giuseppe De Rosa 1,2 1 Department of Medical Sciences, University of Turin, 10126 Turin, Italy; [email protected] (S.C.); [email protected] (S.M.P.); [email protected] (A.T.); [email protected] (E.G.); [email protected] (E.L.); [email protected] (F.G.D.R.) 2 Tufts University School of Medicine, Boston, MA 02129, USA 3 Infectious Diseases Unit, Cardinal Massaia Hospital, 14100 Asti, Italy 4 Microbiology and Virology Unit, University of Turin, 10126 Turin, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-0141-486-404 or +39-3462-248-637 Abstract: Background: Antimicrobial de-escalation (ADE) is a part of antimicrobial stewardship strategies aiming to minimize unnecessary or inappropriate antibiotic exposure to decrease the rate of antimicrobial resistance. Information regarding the effectiveness and safety of ADE in the setting of emergency medicine wards (EMW) is lacking. Methods: Adult patients admitted to EMW and receiving empiric antimicrobial treatment were retrospectively studied. The primary outcome was the rate and timing of ADE. Secondary outcomes included factors associated with early ADE, length of stay, and in-hospital mortality. Results: A total of 336 patients were studied. An initial regimen combining two agents was prescribed in 54.8%. Ureidopenicillins and carbapenems were Citation: Corcione, S.; Mornese the most frequently empiric treatment prescribed (25.1% and 13.6%). -
An Introduction to R Notes on R: a Programming Environment for Data Analysis and Graphics Version 4.1.1 (2021-08-10)
An Introduction to R Notes on R: A Programming Environment for Data Analysis and Graphics Version 4.1.1 (2021-08-10) W. N. Venables, D. M. Smith and the R Core Team This manual is for R, version 4.1.1 (2021-08-10). Copyright c 1990 W. N. Venables Copyright c 1992 W. N. Venables & D. M. Smith Copyright c 1997 R. Gentleman & R. Ihaka Copyright c 1997, 1998 M. Maechler Copyright c 1999{2021 R Core Team Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into an- other language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team. i Table of Contents Preface :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 1 1 Introduction and preliminaries :::::::::::::::::::::::::::::::: 2 1.1 The R environment :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 2 1.2 Related software and documentation ::::::::::::::::::::::::::::::::::::::::::::::: 2 1.3 R and statistics :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 2 1.4 R and the window system :::::::::::::::::::::::::::::::::::::::::::::::::::::::::: -
A Case-Guided Tutorial to Statistical Analysis and Plagiarism Detection
38HIPPOKRATIA 2010, 14 (Suppl 1): 38-48 PASCHOS KA REVIEW ARTICLE Revisiting Information Technology tools serving authorship and editorship: a case-guided tutorial to statistical analysis and plagiarism detection Bamidis PD, Lithari C, Konstantinidis ST Lab of Medical Informatics, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece Abstract With the number of scientific papers published in journals, conference proceedings, and international literature ever increas- ing, authors and reviewers are not only facilitated with an abundance of information, but unfortunately continuously con- fronted with risks associated with the erroneous copy of another’s material. In parallel, Information Communication Tech- nology (ICT) tools provide to researchers novel and continuously more effective ways to analyze and present their work. Software tools regarding statistical analysis offer scientists the chance to validate their work and enhance the quality of published papers. Moreover, from the reviewers and the editor’s perspective, it is now possible to ensure the (text-content) originality of a scientific article with automated software tools for plagiarism detection. In this paper, we provide a step-by- step demonstration of two categories of tools, namely, statistical analysis and plagiarism detection. The aim is not to come up with a specific tool recommendation, but rather to provide useful guidelines on the proper use and efficiency of either category of tools. In the context of this special issue, this paper offers a useful tutorial to specific problems concerned with scientific writing and review discourse. A specific neuroscience experimental case example is utilized to illustrate the young researcher’s statistical analysis burden, while a test scenario is purpose-built using open access journal articles to exemplify the use and comparative outputs of seven plagiarism detection software pieces. -
Modeling Data with Functional Programming in R 2 Preface
Brian Lee Yung Rowe Modeling Data With Functional Programming In R 2 Preface This book is about programming. Not just any programming, but program- ming for data science and numerical systems. This type of programming usually starts as a mathematical modeling problem that needs to be trans- lated into computer code. With functional programming, the same reasoning used for the mathematical model can be used for the software model. This not only reduces the impedance mismatch between model and code, it also makes code easier to understand, maintain, change, and reuse. Functional program- ming is the conceptual force that binds the these two models together. Most books that cover numerical and/or quantitative methods focus primarily on the mathematics of the model. Once this model is established the computa- tional algorithms are presented without fanfare as imperative, step-by-step, algorithms. These detailed steps are designed for machines. It is often difficult to reason about the algorithm in a way that can meaningfully leverage the properties of the mathematical model. This is a shame because mathematical models are often quite beautiful and elegant yet are transformed into ugly and cumbersome software. This unfortunate outcome is exacerbated by the real world, which is messy: data does not always behave as desired; data sources change; computational power is not always as great as we wish; re- porting and validation workflows complicate model implementations. Most theoretical books ignore the practical aspects of working in thefield. The need for a theoretical and structured bridge from the quantitative methods to programming has grown as data science and the computational sciences become more pervasive. -
The Role of Adipokines in Obesity-Associated Asthma
The role of adipokines in obesity-associated asthma By David Gibeon A thesis submitted to Imperial College London for the degree of Doctor of Philosophy in the Faculty of Medicine 2016 National Heart and Lung Institute Dovehouse Street, London SW3 6LY 1 Author’s declaration The following tests on patients were carried out by myself and nurses in the asthma clinic at the Royal Brompton Hospital: lung function measurements, exhaled nitric oxide (FENO) measurement, skin prick testing, methacholine provocation test (PC20), weight, height, waist/hip measurement, bioelectrical impedance analysis (BIA), and skin fold measurements. Fibreoptic bronchoscopies were performed by me and previous research fellows in the Airways Disease Section at the National Heart and Lung Institute (NHLI), Imperial College London. The experiments carried out in this PhD were carried out using the latest equipment available to me at the NHLI. The staining of bronchoalveolar lavage cytospins with Oil red O (Chapter 4) and the staining of endobronchial biopsies with perilipin (Chapter 5) was performed by Dr. Jie Zhu. The multiplex assay (Chapter 7) was performed by Dr. Christos Rossios. The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work. Signed………………………………… David Gibeon 2 Abstract Obesity is a risk factor for the development of asthma and plays a role in disease control, severity and airway inflammation. -
Pedro Valero Mora Universitat De València I Have Worn Many Hats
DYNAMIC INTERACTIVE GRAPHICS PEDRO VALERO MORA UNIVERSITAT DE VALÈNCIA I HAVE WORN MANY HATS • Degree in Psycology • Phd on Human Computer Interaction (HCI): Formal Methods for Evaluation of Interfaces • Teaching Statistics in the Department of Psychology since1990, Full Professor (Catedrático) in 2012 • Research interest in Statistical Graphics, Computational Statistics • Comercial Packages (1995-) Statview, DataDesk, JMP, Systat, SPSS (of course) • Non Comercial 1998- Programming in Lisp-Stat, contributor to ViSta (free statistical package) • Book on Interactive Dynamic Graphics 2006 (with Forrest Young and Michael Friendly). Wiley • Editor of two special issues of the Journal of Statistical Software (User interfaces for R and the Health of Lisp-Stat) • Papers, conferences, seminars, etc. DYNAMIC-INTERACTIVE GRAPHICS • Working on this topic since mid 90s • Other similar topics are visualization, computer graphics, etc. • They are converging in the last few years • I see three periods in DIG • Special hardware • Desktop computers • The internet...and beyond • This presentation will make a review of the History of DIG and will draw lessons from its evolution 1. THE SPECIAL HARDWARE PERIOD • Tukey's Prim 9 • Tukey was not the only one, in 1988 a book summarized the experiences of many researchers on this topic • Lesson#1: Hire a genius and give him unlimited resources, it always works • Or not... • Great ideas but for limited audience, not only because the cost but also the complexity… 2. DESKTOP COMPUTERS • About 1990, the audience augments...macintosh users • Many things only possible previously for people with deep pockets were now possible for…the price of a Mac • Not cheap but affordable • Several packages with a graphical user interface: • Commercial: Statview, DataDesk, SuperANOVA (yes super), JMP, Systat… • Non Commercial: Lisp-Stat, ViSta, XGobi, MANET.. -
Análisis Y Proceso De Datos Aplicado a La Psicología ---Práctica Con
Análisis y proceso de datos aplicado a la Psicología -----Práctica con ordenador----- Primera sesión de contenidos: El paquete estadístico SPSS: Descripción general y aplicación al proceso de datos Profs.: J. Gabriel Molina María F. Rodrigo Documento PowerPoint de uso exclusivo para los alumnos matriculados en la asignatura y con los profesores arriba citados. No está permitida la distribución o utilización no autorizada de este documento. El paquete estadístico SPSS: Descripción general y aplicación al proceso de datos. Contenidos: 1 El paquete estadístico SPSS: aspectos generales y descripción del funcionamiento. 2 Proceso de datos con SPSS: introducción, edición y almacenamiento de archivos de datos. 1.1 Estructura general: barra de menús, ventanas, barras de herramientas, barra de estado... (1) Programas orientados al análisis de datos : los paquetes estadísticos (BMDP, R, S-PLUS, DataDesk, Jump, Minitab, SAS, Statgraphics, Statview, Systat, ViSta...) (2) Puesta en marcha del programa SPSS Inicio >> Programas >> SPSS for Windows >> SPSS 11.0 para Windows (3) Abrir el archivo de datos ‘demo.sav’ Menú Archivo >> Abrir >> Datos... (C:) / Archivos de Programas / SPSS / tutorial / sample files / 1.2 Introducción a la utilización de SPSS: un recorrido por las funciones básicas del programa. Menú ? >> Tutorial >> Libro ‘Introducción’ 1.3 Tipos de documento asociados al programa • Documentos de datos (.sav) << Editor de datos de SPSS (Documento SPSS) • Documentos de resultados (.spo) << Visor SPSS (Documento de Visor) Visualizacion de documentos de datos y de resultados (1) Abrir el fichero de resultados ‘viewertut.spo’ Menú Archivo >> Abrir >> Resultados... (C:) / Archivos de Programas / SPSS / tutorial / sample files / (2) Abrir el fichero de datos ‘Ansiedad.sav’ Menú Archivo >> Abrir >> Datos.. -
The R Project for Statistical Computing a Free Software Environment For
The R Project for Statistical Computing A free software environment for statistical computing and graphics that runs on a wide variety of UNIX platforms, Windows and MacOS OpenStat OpenStat is a general-purpose statistics package that you can download and install for free. It was originally written as an aid in the teaching of statistics to students enrolled in a social science program. It has been expanded to provide procedures useful in a wide variety of disciplines. It has a similar interface to SPSS SOFA A basic, user-friendly, open-source statistics, analysis, and reporting package PSPP PSPP is a program for statistical analysis of sampled data. It is a free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions TANAGRA A free, open-source, easy to use data-mining package PAST PAST is a package created with the palaeontologist in mind but has been adopted by users in other disciplines. It’s easy to use and includes a large selection of common statistical, plotting and modelling functions AnSWR AnSWR is a software system for coordinating and conducting large-scale, team-based analysis projects that integrate qualitative and quantitative techniques MIX An Excel-based tool for meta-analysis Free Statistical Software This page links to free software packages that you can download and install on your computer from StatPages.org Free Statistical Software This page links to free software packages that you can download and install on your computer from freestatistics.info Free Software Information and links from the Resources for Methods in Evaluation and Social Research site You can sort the table below by clicking on the column names. -
From Datasets to Resultssets in Stata
From datasets to resultssets in Stata Roger Newson King's College London, London, UK [email protected] http://www.kcl-phs.org.uk/rogernewson/ Distributed at the 10th UK Stata Users' Group Meeting on 29 June 2004 1 What are resultssets? A resultsset is a Stata dataset created as output by a Stata command. It may be simply listed to the Stata log and/or output to a disk ¯le and/or written to the memory, overwriting any pre-existing dataset. If you are a SAS user converting to Stata, then note that Stata datasets do the job of SAS data sets, and Stata resultssets do the job of SAS output data sets. 1.1 Why resultssets? In general, a Stata dataset, or a dataset in any other format, should contain one observation per thing, and data on attributes of things. For instance, in the medical sector, a dataset might have one observation per patient, and data on the patient's baseline characteristics. Alternatively, a dataset might have one observation per visit to a health centre, and data on the state of the patient who made the visit. Usually, the variables in a dataset are either primary key variables, which identify the things corresponding to the observations, or non-key variables, which identify interesting attributes of those things. For instance, if there is one observation per patient, then one of the variables is usually a patient ID number, which identi¯es the observation uniquely. Or, if there is one observation per visit, and a patient may only make one visit per day, then the primary key variables are usually patient ID and visit date. -
Symbolic Formulae for Linear Mixed Models Arxiv:1911.08628V1 [Stat
Symbolic Formulae for Linear Mixed Models∗ Emi Tanaka1,2,* Francis K. C. Hui3 1 School of Mathematics and Statistics, The University of Sydney, NSW, Australia, 2006 2 Department of Econometrics and Business Statistics, Monash University, VIC, Australia, 3800 3 Research School of Finance, Actuarial Studies & Statistics, Australian National University, ACT, Australia, 2601 < [email protected] Abstract A statistical model is a mathematical representation of an often simpli- fied or idealised data-generating process. In this paper, we focus on a par- ticular type of statistical model, called linear mixed models (LMMs), that is widely used in many disciplines e.g. agriculture, ecology, econometrics, psychology. Mixed models, also commonly known as multi-level, nested, hierarchical or panel data models, incorporate a combination of fixed and random effects, with LMMs being a special case. The inclusion of random effects in particular gives LMMs considerable flexibility in accounting for many types of complex correlated structures often found in data. This flex- arXiv:1911.08628v1 [stat.ME] 19 Nov 2019 ibility, however, has given rise to a number of ways by which an end-user can specify the precise form of the LMM that they wish to fit in statistical software. In this paper, we review the software design for specification of the LMM (and its special case, the linear model), focusing in particular on the use of high-level symbolic model formulae and two popular but contrasting R-packages in lme4 and asreml. ∗Supported by R Consortium 1 1 Introduction Statistical models are mathematical formulation of often simplified real world phe- nomena, the use of which is ubiquitous in many data analyses.