The Unscrambler.Pdf

Total Page:16

File Type:pdf, Size:1020Kb

The Unscrambler.Pdf Leading all-in-one Multivariate Data Analysis and Design of Experiments software, now even more powerful and easy to use. Powerful multivariate Easy data importing Outstanding graphics, analysis methods and options with intuitive plots and interactive data design of experiments worklows and interface visualization tools “ Cutting through complex data “ This intelligent engine borders “ sets to underlying structures...is upon data mining, as it cuts through “ simplicity itself prediction and classiication problems Bring data to life 02 CAMO The Unscrambler® X The Unscrambler® X 03 CAMO GET DEEPER INSIGHTS FROM YOUR DATA, FASTER AND EASIER TURN YOUR DATA INTO A COMPETITIVE ADVANTAGE The Unscrambler® X is world-leading data mining and predictive modelling software used by over 25,000 data analysts, The powerful analytical tools in The Unscrambler® X let you discover underlying patterns in large data sets, understand researchers, engineers and scientists worldwide. The latest version builds on its tradition of powerful multivariate analytical processes and build better predictive models. This enables you to make more informed, data-driven decisions, reduce R&D methods and ease of use, adding even greater calculation eficiency and performance. costs, improve manufacturing processes, product quality and time to market. New to version 10.2 Software for every industry The Unscrambler® X version 10.2 has several new analytical methods and For over 25 years, The Unscrambler® has enabled organizations across import options, as well as a wide range of added features throughout the a broad cross section of industries and research ields to combine their software for improved usability and security. See different plots all on the industry expertise with deep data insights. Support Vector Machine Regression (SVMR) has been added same screen for easier Aerospace Research & Academia data interpretation Agriculture Retail Compliance Mode has been added as an installation option for Powerful regression, organizations that must meet the requirements of electronic signature Automotive Semi-conductors classification, exploratory data and records handling Chemicals/Petrochem Engineering analysis and classical statistics Recalculate With New is added as a new feature to PCA, PCR, PLS, Electronics Food & Beverage which allows the addition of new data to an existing model Energy/Renewables Manufacturing Digital signatures have been added for enhanced data integrity Oil & Gas Marketing Blocking of Designs added to Full Factorial designs in the Design of Pharmaceuticals Medical Devices Experiments module Pulp & Paper Mining & Metals Enhanced security features Three new spectroscopy vendor speciic imports have been included including compliance mode, An Interpolation function has been added digital signatures and audit trail Extensive data pre-processing Powerful data analysis tools tools including spectral Exploratory data analysis Application areas transformations Regression and classiication Our advanced yet easy to use software is designed to be lexible for many Predictive modeling different data analysis needs. The Unscrambler® X is used by companies and researchers in applications including: Design of Experiments Data pre-processing Research & Development Classical statistics Customer segmentation / Marketing Intuitive project based workflows Manufacturing, production & engineering Drag ’n’ drop data directly from make it easier to manage your Quality assurance & control Excel or import from scientific daily work instruments General data mining & analysis Using The Unscrambler, we Six Sigma / Lean manufacturing “ were able to resolve a product quality problem which has saved us $1M per year. It also gave us The Unscrambler is much “ better process understanding “ more intuitive and has all Comprehensive tutorials on which we have used to optimize the features I need plus more “ Interactive data visualization multivariate analysis and using other manufacturing processes advanced methods than tools: zoom, rotate and drill down the software to individual data points Siri Sølberg, Senior Process Engineer, Nidar AS generalist statistical software Søren Bech, Head of Research, Bang & Olufsen Download a free trial at www.camo.com Download a free trial at www.camo.com > Bring data to life > camo.com > Bring data to life > camo.com FEATURES OF THE UNSCRAMBLER® X VERSION 10.2 Exploratory Data Analysis Regression and Classiication Data Pretreatments Design Of Experiments Descriptive Statistics Regression Methods Spectral Functions Intuitive Design Wizard with full General Data Summary Tools Min/Max and Multiple Linear Regression (MLR)/Principal Smoothing, Derivatives: Moving Average/ descriptions and Beginner/Expert modes Mean Chart NEW Component Regression (PCR) and Partial Norris Gap/Savitsky-Golay, Baseline Complete range of full and fractional Statistical Tests Least Squares Regression (PLSR) Correction factorial designs Univariate Statistical Tools, Including t-test, Support Vector Machine Regression and Normalization Enhanced optimization designs including F-tests etc. Prediction NEW Scatter Correction /Advanced Functions Central Composite (CCD) and Contingency Analysis NEW Choice of algorithms, NIPALS and SVD Multiplicative and Extended Multiplicative Box-Behnken (BB) designs for PCR and NIPALS, Kernel Methods and Mixture designs including Axial, Simplex Cluster Analysis Scatter Correction (MSC/EMSC) Orthogonal Scores for PLSR Lattice and Simplex Centroid designs K-Means Standard Normal Variate (SNV) Improved Test Set Validation options and Hierarchical Cluster Analysis Orthogonal Signal Correction (OSC) New Blocking of Full Factorial Designs NEW Test Scores added NEW Algorithm NEW Principal Component Analysis (PCA) Comprehensive Analysis Overview L-PLS, incorporating three data tables for Deresolve, Detrending Choice of using NIPALS or SVD algorithms ANOVA tables and other tabular results greater insights into data structure Interpolation NEW Rotation methods including Varimax, Cube Plots Advanced Classiication Methods Equimax, Quartimax and Parsimax General Transforms Response Surfaces Projection, Soft Independent Modelling of Improved Centre and Scale options Analysis of Effects Multivariate Curve Resolution (MCR) Class Analogy (SIMCA), Linear Discriminant Spectroscopic: Relectance/Transmission/ Interactive Tables Resolve time evolving data such as Analysis (LDA), Support Vector Machines Kubelka-Munck chemical reaction or chromatographic data (SVM) Classiication with numerous kernel Interaction & Squares and Individual into pure constituent proiles and pure types Variable Weighting spectra Compute General Quantile Normalization For a full feature list and system requirements Compliant with 21 CFR Part 11 Correlation Optimization Warping (COW) please visit www.camo.com (Electronic records) Beneits of The Unscrambler® X Multivariate data analysis tools Flexible & adaptable for different uses Ideal for large & complex data sets Integrated Design of Experiments Intuitive & user-friendly Works with MyInstrument Driver Affordable & value for money Easy data importing ODBC compatible and OPC connectivity “ The new version“ is even more intuitive and easy to use, especially for new users Dr Garth Maker, Lecturer in Pharmaceutical Chemistry, Murdoch University, Western Australia Find out more For more information please contact your regional CAMO ofice or email [email protected] www.camo.com NORWAY USA INDIA JAPAN AUSTRALIA Nedre Vollgate 8, One Woodbridge Center 14 & 15, Krishna Reddy Shibuya 3-chome Square Bldg 2F PO Box 97 N-0158 Suite 319, Woodbridge Colony, Domlur Layout 3-5-16 Shibuya Shibuya-ku St Peters Oslo NJ 07095 Bangalore - 560 071 Tokyo, 150-0002 NSW, 2044 Tel: (+47) 223 963 00 Tel: (+1) 732 726 9200 Tel: (+91) 80 4125 4242 Tel: (+81) 3 6868 7669 Tel: (+61) 4 0888 2007 Fax: (+47) 223 963 22 Fax: (+1) 973 556 1229 Fax: (+91) 80 4125 4181 Fax: (+81) 3 6730 9539.
Recommended publications
  • Primena Statistike U Kliničkim Istraţivanjima Sa Osvrtom Na Korišćenje Računarskih Programa
    UNIVERZITET U BEOGRADU MATEMATIČKI FAKULTET Dušica V. Gavrilović Primena statistike u kliničkim istraţivanjima sa osvrtom na korišćenje računarskih programa - Master rad - Mentor: prof. dr Vesna Jevremović Beograd, 2013. godine Zahvalnica Ovaj rad bi bilo veoma teško napisati da nisam imala stručnu podršku, kvalitetne sugestije i reviziju, pomoć prijatelja, razumevanje kolega i beskrajnu podršku porodice. To su razlozi zbog kojih želim da se zahvalim: . Mom mentoru, prof. dr Vesni Jevremović sa Matematičkog fakulteta Univerziteta u Beogradu, koja je bila ne samo idejni tvorac ovog rada već i dugogodišnja podrška u njegovoj realizaciji. Njena neverovatna upornost, razne sugestije, neiscrpni optimizam, profesionalizam i razumevanje, predstavljali su moj stalni izvor snage na ovom master-putu. Članu komisije, doc. dr Zorici Stanimirović sa Matematičkog fakulteta Univerziteta u Beogradu, na izuzetnoj ekspeditivnosti, stručnoj recenziji, razumevanju, strpljenju i brojnim korisnim savetima. Članu komisije, mr Marku Obradoviću sa Matematičkog fakulteta Univerziteta u Beogradu, na stručnoj i prijateljskoj podršci kao i spremnosti na saradnju. Dipl. mat. Radojki Pavlović, šefu studentske službe Matematičkog fakulteta Univerziteta u Beogradu, na upornosti, snalažljivosti i kreativnosti u pronalaženju raznih ideja, predloga i rešenja na putu realizacije ovog master rada. Dugogodišnje prijateljstvo sa njom oduvek beskrajno cenim i oduvek mi mnogo znači. Dipl. mat. Zorani Bizetić, načelniku Data Centra Instituta za onkologiju i radiologiju Srbije, na upornosti, idejama, detaljnoj reviziji, korisnim sugestijama i svakojakoj podršci. Čak i kada je neverovatno ili dosadno ili pametno uporna, mnogo je i dugo volim – skoro ceo moj život. Mast. biol. Jelici Novaković na strpljenju, reviziji, bezbrojnim korekcijama i tehničkoj podršci svake vrste. Hvala na osmehu, budnom oku u sitne sate, izvrsnoj hrani koja me je vraćala u život, nes-kafi sa penom i transfuziji energije kada sam bila na rezervi.
    [Show full text]
  • Comparison of Hyperspectral Imaging and Near-Infrared Spectroscopy to Determine Nitrogen and Carbon Concentrations in Wheat
    remote sensing Article Comparison of Hyperspectral Imaging and Near-Infrared Spectroscopy to Determine Nitrogen and Carbon Concentrations in Wheat Iman Tahmasbian 1,* , Natalie K. Morgan 2, Shahla Hosseini Bai 3, Mark W. Dunlop 1 and Amy F. Moss 2 1 Department of Agriculture and Fisheries, Queensland Government, Toowoomba, QLD 4350, Australia; Scopus affiliation ID: 60028929; [email protected] 2 School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia; [email protected] (N.K.M.); [email protected] (A.F.M.) 3 Centre for Planetary Health and Food Security, School of Environment and Science, Griffith University, Brisbane, QLD 4111, Australia; s.hosseini-bai@griffith.edu.au * Correspondence: [email protected] Abstract: Hyperspectral imaging (HSI) is an emerging rapid and non-destructive technology that has promising application within feed mills and processing plants in poultry and other intensive animal industries. HSI may be advantageous over near infrared spectroscopy (NIRS) as it scans entire samples, which enables compositional gradients and sample heterogenicity to be visualised and analysed. This study was a preliminary investigation to compare the performance of HSI with that of NIRS for quality measurements of ground samples of Australian wheat and to identify the most important spectral regions for predicting carbon (C) and nitrogen (N) concentrations. In total, 69 samples were scanned using an NIRS (400–2500 nm), and two HSI cameras operated in Citation: Tahmasbian, I.; Morgan, 400–1000 nm (VNIR) and 1000–2500 nm (SWIR) spectral regions. Partial least square regression N.K; Hosseini Bai, S.; Dunlop, M.W; (PLSR) models were used to correlate C and N concentrations of 63 calibration samples with their Moss, A.F Comparison of spectral reflectance, with 6 additional samples used for testing the models.
    [Show full text]
  • Construction of a Neuro-Immune-Cognitive Pathway-Phenotype Underpinning the Phenome Of
    Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 October 2019 doi:10.20944/preprints201910.0239.v1 Construction of a neuro-immune-cognitive pathway-phenotype underpinning the phenome of deficit schizophrenia. Hussein Kadhem Al-Hakeima, Abbas F. Almullab, Arafat Hussein Al-Dujailic, Michael Maes d,e,f. a Department of Chemistry, College of Science, University of Kufa, Iraq. E-mail: [email protected]. b Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf, Iraq. E-mail: [email protected]. c Senior Clinical Psychiatrist, Faculty of Medicine, Kufa University. E-mail: [email protected]. d* Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; e Department of Psychiatry, Medical University of Plovdiv, Plovdiv, Bulgaria; f IMPACT Strategic Research Centre, Deakin University, PO Box 281, Geelong, VIC, 3220, Australia. Corresponding author Prof. Dr. Michael Maes, M.D., Ph.D. Department of Psychiatry Faculty of Medicine Chulalongkorn University Bangkok Thailand 1 © 2019 by the author(s). Distributed under a Creative Commons CC BY license. Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 October 2019 doi:10.20944/preprints201910.0239.v1 https://scholar.google.co.th/citations?user=1wzMZ7UAAAAJ&hl=th&oi=ao [email protected]. 2 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 October 2019 doi:10.20944/preprints201910.0239.v1 Abstract In schizophrenia, pathway-genotypes may be constructed by combining interrelated immune biomarkers with changes in specific neurocognitive functions that represent aberrations in brain neuronal circuits. These constructs provide insight on the phenome of schizophrenia and show how pathway-phenotypes mediate the effects of genome X environmentome interactions on the symptomatology/phenomenology of schizophrenia.
    [Show full text]
  • Predicting Plant Species Richness and Vegetation Patterns in Cultural Landscapes Using Disturbance Parameters
    Agriculture, Ecosystems and Environment 122 (2007) 446–452 www.elsevier.com/locate/agee Predicting plant species richness and vegetation patterns in cultural landscapes using disturbance parameters C. Buhk a,*, V. Retzer b, C. Beierkuhnlein b, A. Jentsch a a Disturbance Ecology and Vegetation Dynamics, Helmholtz Centre for Environmental Research – UFZ, Permoserstr. 15, 04318 Leipzig, Germany and Bayreuth University, 95440 Bayreuth, Germany b Biogeography, University of Bayreuth, Universita¨tsstr. 30, 95440 Bayreuth, Germany Received 1 August 2006; received in revised form 22 February 2007; accepted 27 February 2007 Available online 24 April 2007 Abstract A new methodological framework for plant diversity assessment at the landscape scale is presented that exhibits the following strengths: (1) potential for easily standardizable sampling procedure; (2) characterization of disturbance regime; (3) use of selected disturbance descriptors as explanatory variables which probably allow for better transferability than site specific land use types—for example, to evaluate the emerging use of energy plants that pose novel management challenges without historic precedence to many landscapes; (4) analysis of quantitative and qualitative aspects of plant species diversity (alpha and beta diversity). For data analysis, a powerful regression method (PLS- R) was applied. On this basis, after further validation and transferability tests, a practical tool for the development and validation of effective agri-environmental programmes may be developed. # 2007 Elsevier B.V. All rights reserved. Keywords: Agri-environmental programmes; Alpha diversity; Beta diversity; Fichtelgebirge; Land use; Disturbance; Pattern analysis 1. Introduction paid per ha of arable land or grassland managed, and are no longer subsidized according to the quantity of certain goods The EU Sustainable Development Strategy, launched by produced or land use activity maintained.
    [Show full text]
  • Use of Pyrolysis Mass Spectrometry with Supervised Learning for The
    Use of Pyrolysis Mass Spectrom etry with Supervised Learning for the Assessm ent of the Adulteration of Milk of Different Species ROYSTON GOODACRE Institute of Biological Sciences, University of Wales, Aberystwyth, Dyfed, SY23 3DA, U.K. Binary m ixtures of 0± 20% cows’ m ilk with ewes’ m ilk, 0± 20% raphy;3,4 (2) electrophoretic methods including gel elec- cows’ m ilk with goats’ m ilk, and 0± 5% cow s’ m ilk with goats’ m ilk trophoresis 5,6 and isoelectric focusing;7,8 and (3) immu- were subjected to pyrolysis m ass spectrom etry (PyMS). For an alysis nological-based methods such as agar-gel immunodiffu- of the pyrolysis m ass sp ectra so as to determ ine the p ercentage sion,8± 10 immunoelectrophore sis,11 immunodotti ng,12 adulteration of either caprine or ovine m ilk w ith bovine m ilk, par- 13 tial least-sq uares regression (PLS), p rincipal com ponents regression haemagglutination, and various methods based on the 14± 16 (PCR) and fully intercon nected feed-forward ar ti® cial neural net- enzyme-linked immunosorbent assay (ELISA). works (ANNs) were studied. In the latter case, the w eights were Pyrolysis mass spectrometry (PyMS) is a rapid, auto- m odi® ed by u sing the stan dard b ack-prop agation algor ith m , and mated, instrument-based technique that permits the ac- the nodes u sed a sigm oidal squ ash ing function. It was fou nd that quisition of spectroscopic data from 300 or more samples each of the m ethods could be u sed to provid e calibration m odels per working day.
    [Show full text]
  • IMPROVEMENT of MS BASED E-NOSE PERFORMANCES by INCORPORATION of CHROMATOGRAPHIC RETENTION TIME AS a NEW DATA DIMENSION Cosmin Burian
    IMPROVEMENT OF MS BASED E-NOSE PERFORMANCES BY INCORPORATION OF CHROMATOGRAPHIC RETENTION TIME AS A NEW DATA DIMENSION Cosmin Burian ISBN: 978-84-694-0293-1 Dipòsit Legal: T-202-2011 ADVERTIMENT. La consulta d’aquesta tesi queda condicionada a l’acceptació de les següents condicions d'ús: La difusió d’aquesta tesi per mitjà del servei TDX (www.tesisenxarxa.net) ha estat autoritzada pels titulars dels drets de propietat intel·lectual únicament per a usos privats emmarcats en activitats d’investigació i docència. No s’autoritza la seva reproducció amb finalitats de lucre ni la seva difusió i posada a disposició des d’un lloc aliè al servei TDX. No s’autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant al resum de presentació de la tesi com als seus continguts. En la utilització o cita de parts de la tesi és obligat indicar el nom de la persona autora. ADVERTENCIA. La consulta de esta tesis queda condicionada a la aceptación de las siguientes condiciones de uso: La difusión de esta tesis por medio del servicio TDR (www.tesisenred.net) ha sido autorizada por los titulares de los derechos de propiedad intelectual únicamente para usos privados enmarcados en actividades de investigación y docencia. No se autoriza su reproducción con finalidades de lucro ni su difusión y puesta a disposición desde un sitio ajeno al servicio TDR. No se autoriza la presentación de su contenido en una ventana o marco ajeno a TDR (framing). Esta reserva de derechos afecta tanto al resumen de presentación de la tesis como a sus contenidos.
    [Show full text]
  • All-In-One Multivariate Data Analysis and Design of Experiments Software
    Bring data to life Version 10.3 All-in-one Multivariate Data Analysis and Design of Experiments software Powerful multivariate Easy data importing Outstanding graphics, analysis methods and options with intuitive plots and interactive data design of experiments workflows and interface visualization tools “ “ Cutting through complex“ data This intelligent engine borders upon data sets to underlying structures... “mining, as it cuts through prediction and is simplicity itself classification problems 02 CAMO The Unscrambler® X The Unscrambler is much more intuitive“ and has “all the features I need plus more advanced methods than generalist statistical software Søren Bech, Head of Research, Bang & Olufsen The Unscrambler® X 03 CAMO Software for every industry For almost 30 years, The Unscrambler® has enabled organizations across many industries and research fields to improve product development, process understanding and quality control through deeper data insights. Pharmaceuticals Energy/Renewables Chemicals/Petrochem Automotive Agriculture Medical Devices Food & Beverage Electronics Pulp & Paper Engineering Mining & Metals Retail Oil & Gas Semi-conductors Manufacturing Marketing Research & Academia Aerospace 04 CAMO The Unscrambler® X Multivariate data analysis is a highly visual approach The Unscrambler® X is the only major multivariate data that helps you identify and understand patterns in large analysis software that includes a seamlessly integrated or complex data sets. Easily accessible raw data plots Design of Experiments (DoE) module, giving you a are a very useful tool in the analysis. powerful all-in-one tool for your data analysis needs. In the 3D Scatter Plot above, data from paper Multivariate analysis and Design of Experiments often go manufacturing is shown, where each of the samples hand in hand.
    [Show full text]
  • Consumer Perception of Wood Surfaces: the Relationship Between Stated Preferences and Visual Homogeneity
    J Wood Sci (2010) 56:276–283 © The Japan Wood Research Society 2010 DOI 10.1007/s10086-009-1104-7 ORIGINAL ARTICLE Olav Høibø · Anders Q. Nyrud Consumer perception of wood surfaces: the relationship between stated preferences and visual homogeneity Received: July 6, 2009 / Accepted: December 21, 2009 / Published online: March 23, 2010 Abstract Information about people’s preferences as to wood products and to building design and construction. wood products is of relevance to several decision makers in More knowledge about the appearance of wood can provide the forest sector. Studies revealing consumer preference competitive advantages for the forest industry and will also, provide information that can be used for marketing and if applied to the development of new products in accor- manufacturing of wood products, but these also provide dance with consumers’ needs and requirements, improve information of relevance to designers and decision makers consumer satisfaction and welfare. Preference studies are involved in building design and construction processes. Pre- also relevant from a psychological point of view. vious studies show that the overall harmony of the visual Results from previous preference studies indicate that surface is correlated with preference. In this study, per- people’s preferences are affected by product attributes. ceived visual homogeneity is modeled for fi ve copper- Brandt and Shook1 conducted a comprehensive review of impregnated and fi ve organic biocide-impregnated decking previous attribute research on forest products and con- materials with different visual quality. The models are cluded that consumers’ quality attributions with respect to based on visual variables. Homogeneity is a function of forest products can usually be ascribed to the visual and material-dependent variables (dry knots, knot shape, and tactile, i.e., tangible, properties of the wood.
    [Show full text]
  • Combining Multivariate Analysis and Pollen Count to Classify Honey Samples Accordingly to Different Botanical Origins
    SCIENTIFIC NOTE COMBINING MULTIVARIATE ANALYSIS AND POLLEN COUNT TO CLASSIFY HONEY SAMPLES ACCORDINGLY TO DIFFERENT BOTANICAL ORIGINS Eduardo Corbella1, and Daniel Cozzolino2* A B S T R A C T INTRODUCTION This study reports the combination of multivariate Scientists in the food and beverage industries are techniques and pollen count analysis to classify hon- interested in identifying the main changes in proc- ey samples according to botanical sources, in sam- ess that may lead to a change in quality or compro- ples from Uruguay. Honey samples from different mises in any ingredient or finished products. Food botanical origins, namely Eucalyptus spp. (n = 10), authenticity issues in the form of adulteration and Lotus spp. (n = 12), Salix spp. (n = 5), “mil flores” improper description have been around for a long (Myrtaceae spp.) (n = 12) and coronilla (Scutia buxi- time. Recently, the demand for natural honey has folia Reissek) (n = 10) were analysed using Melisso- increased, consequently, methods to assure the au- palynology (pollen identification). Principal compo- thenticity of honey can be economically important. nent analysis (PCA) and linear discriminant analysis (LDA) were used to classify the honey samples ac- Several factors contribute to the quality properties cordingly to their botanical origin based on a pollen of honey, such as high osmotic pressure, lower count. Honey samples of higher percentage (> 70%) water activity, low pH, and low protein content, of Eucalyptus, Lotus and Scutia pollen were 100% cor- among others (Anklam, 1998; Bogdanov, 1999). rectly classified, whilst samples from Myrtaceae spp. and Salix were 80 and 66% correctly classified, re- The authenticity of honey has two aspects, one re- spectively.
    [Show full text]
  • Download This PDF File
    Control Theory and Informatics www.iiste.org ISSN 2224-5774 (print) ISSN 2225-0492 (online) Vol 2, No.1, 2012 The Trend Analysis of the Level of Fin-Metrics and E-Stat Tools for Research Data Analysis in the Digital Immigrant Age Momoh Saliu Musa Department of Marketing, Federal Polytechnic, P.M.B 13, Auchi, Nigeria. Tel: +2347032739670 e-mail: [email protected] Shaib Ismail Omade (Corresponding author) Department of Statistics, School of Information and Communication Technology, Federal Polytechnic, P.M.B 13, Auchi, Nigeria. Phone: +2347032808765 e-mail: [email protected] Abstract The current trend in the information technology age has taken over every spare of human discipline ranging from communication, business, governance, defense to education world as the survival of these sectors depend largely on the research outputs for innovation and development. This study evaluated the trend of the usage of fin-metrics and e-stat tools application among the researchers in their research outputs- digital data presentation and analysis in the various journal outlets. The data used for the study were sourced primarily from the sample of 1720 out of 3823 empirical on and off line journals from various science and social sciences fields. Statistical analysis was conducted to evaluate the consistency of use of the digital tools in the methodology of the research outputs. Model for measuring the chance of acceptance and originality of the research was established. The Cockhran test and Bartlet Statistic revealed that there were significant relationship among the research from the Polytechnic, University and other institution in Nigeria and beyond. It also showed that most researchers still appeal to manual rather than digital which hampered the input internationally and found to be peculiar among lecturers in the system that have not yet appreciate IT penetration in Learning.
    [Show full text]
  • 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.
    [Show full text]
  • A Complete Data Handling Package for NMR Metabolomics Bradley Worley University of Nebraska-Lincoln, [email protected]
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Robert Powers Publications Published Research - Department of Chemistry 2014 MVAPACK: A Complete Data Handling Package for NMR Metabolomics Bradley Worley University of Nebraska-Lincoln, [email protected] Robert Powers University of Nebraska-Lincoln, [email protected] Follow this and additional works at: http://digitalcommons.unl.edu/chemistrypowers Part of the Analytical Chemistry Commons Worley, Bradley and Powers, Robert, "MVAPACK: A Complete Data Handling Package for NMR Metabolomics" (2014). Robert Powers Publications. 23. http://digitalcommons.unl.edu/chemistrypowers/23 This Article is brought to you for free and open access by the Published Research - Department of Chemistry at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Robert Powers Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Articles pubs.acs.org/acschemicalbiology MVAPACK: A Complete Data Handling Package for NMR Metabolomics Bradley Worley and Robert Powers* Department of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska 68588-0304, United States *S Supporting Information ABSTRACT: Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set.
    [Show full text]