Common Statistical Packages
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ICT in the Kosovo National Statistical System - Baseline Review and Recommendations for Development
UNDP Kosovo UNKT Technical assistance to the IT department of the Kosovo Agency of Statistics (KAS) Technical analysis of information technology in the national statistical system ICT in the Kosovo National Statistical System - Baseline review and Recommendations for development April 2013 by Arij Dekker, Consultant in statistical data processing and management [email protected] ICT in the Kosovo National Statistical System - Baseline review and Recommendations for development 1 Contents List of Acronyms ...................................................................................................................................... 3 Executive Summary ................................................................................................................................. 5 Chapter 1. Introduction ..................................................................................................................... 7 Chapter 2. Methods of information gathering .................................................................................... 9 2.1 Description of interview partners and question clusters ........................................................... 9 2.2 Other information sources ..................................................................................................... 12 Chapter 3. The present state of ICT in the Kosovo national statistical system ................................... 14 3.1 Summary of information gathered from the interviews ......................................................... -
Curriculum Vitae
CURRICULUM VITAE Name Ankit Patras Address 111 Agricultural and Biotechnology Building, Department of Agricultural and Environmental Sciences, Tennessee State University, Nashville TN 37209 Phone 615-963-6007, 615-963-6019/6018 Email [email protected], [email protected] EDUCATION 2005- 2009: Ph.D. Biosystems Engineering: School of Biosystems Engineering, College of Engineering & Architecture, Institute of Food and Health, University College Dublin, Ireland. 2005- 2006: Post-graduate certificate (Statistics & Computing): Department of Statistics and Actuarial Science, School of Mathematical Sciences, University College Dublin, Ireland 2003- 2004: Master of Science (Bioprocess Technology): UCD School of Biosystems Engineering, College of Engineering & Architecture, University College Dublin, Ireland 1998- 2002: Bachelor of Technology (Agricultural and Food Engineering): Allahabad Agriculture Institute, India ACADEMIC POSITIONS Assistant Professor, Food Biosciences: Department of Agricultural and Environmental Research, College of Agriculture, Human and Natural Sciences, Tennessee State University, Nashville, Tennessee 2nd Jan, 2014 - Present • Leading a team of scientist and graduate students in developing a world-class food research centre addressing current issues in human health, food safety specially virus, bacterial and mycotoxins contamination • Developing a world-class research program on improving safety of foods and pharmaceuticals • Develop cutting edge technologies (i.e. optical technologies, bioplasma, power Ultrasound, -
On New Data Sources for the Production of Official Statistics
On new data sources for the production of official statistics David Salgado1,2 and Bogdan Oancea3 1Dept. Methodology and Development of Statistical Production, Statistics Spain (INE), Spain 2Dept. Statistics and Operations Research, Complutense University of Madrid, Spain 3Dept. Business Administration, University of Bucharest, Romania February 7, 2020 Abstract In the past years we have witnessed the rise of new data sources for the potential production of official statistics, which, by and large, can be classified as survey, administrative, and digital data. Apart from the differences in their generation and collection, we claim that their lack of statistical metadata, their economic value, and their lack of ownership by data holders pose several entangled challenges lurking the incorporation of new data into the routinely production of official statistics. We argue that every challenge must be duly overcome in the international community to bring new statistical products based on these sources. These challenges can be naturally classified into different entangled issues regarding access to data, statistical methodology, quality, information technologies, and management. We identify the most relevant to be necessarily tackled before new data sources can be definitively considered fully incorporated into the production of official statistics. Contents 1 Introduction 2 2 Data: survey, administrative, digital 3 2.1 Somedefinitions ..................................... .... 3 2.2 Statisticalmetadata ................................ ....... 4 2.3 Economicvalue..................................... -
Statistics and GIS Assistance Help with Statistics
Statistics and GIS assistance An arrangement for help and advice with regard to statistics and GIS is now in operation, principally for Master’s students. How do you seek advice? 1. The users, i.e. students at INA, make direct contact with the person whom they think can help and arrange a time for consultation. Remember to be well prepared! 2. Doctoral students and postdocs register the time used in Agresso (if you have questions about this contact Gunnar Jensen). Help with statistics Research scientist Even Bergseng Discipline: Forest economy, forest policies, forest models Statistical expertise: Regression analysis, models with random and fixed effects, controlled/truncated data, some time series modelling, parametric and non-parametric effectiveness analyses Software: Stata, Excel Postdoc. Ole Martin Bollandsås Discipline: Forest production, forest inventory Statistics expertise: Regression analysis, sampling Software: SAS, R Associate Professor Sjur Baardsen Discipline: Econometric analysis of markets in the forest sector Statistical expertise: General, although somewhat “rusty”, expertise in many econometric topics (all-rounder) Software: Shazam, Frontier Associate Professor Terje Gobakken Discipline: GIS og long-term predictions Statistical expertise: Regression analysis, ANOVA and PLS regression Software: SAS, R Ph.D. Student Espen Halvorsen Discipline: Forest economy, forest management planning Statistical expertise: OLS, GLS, hypothesis testing, autocorrelation, ANOVA, categorical data, GLM, ANOVA Software: (partly) Shazam, Minitab og JMP Ph.D. Student Jan Vidar Haukeland Discipline: Nature based tourism Statistical expertise: Regression and factor analysis Software: SPSS Associate Professor Olav Høibø Discipline: Wood technology Statistical expertise: Planning of experiments, regression analysis (linear and non-linear), ANOVA, random and non-random effects, categorical data, multivariate analysis Software: R, JMP, Unscrambler, some SAS Ph.D. -
Eric Brenner, MD – Brief Biosketch: (Update of December 2018) *** Email Contact: [email protected]
Eric Brenner, MD – Brief Biosketch: (Update of December 2018) *** Email contact: [email protected] Eric Brenner is a medical epidemiologist and public health physician who currently resides in Columbia, South Carolina (USA). He attended the University of California at Berkeley where he majored in French Literature. After graduation he joined the Peace Corps and worked as a secondary school teacher in the Ivory Coast (West Africa) for two years. He then attended Dartmouth Medical School and completed subsequent clinical training both in San Francisco and in South Carolina (SC) which led to Board Certification in Internal Medicine and Infectious Disease. He has over 35 years experience with communicable disease control programs having worked at different times at the state level with the SC Department of Health and Environmental Control (SC-DHEC), at the national level with the US Centers for Disease Control (CDC), and internationally with the World Health Organization (WHO) where he worked for a year in Geneva with the Expanded Programme on Immunization (EPI) as well as on short- term assignments in a number of other countries. He has also worked as a consultant with other international agencies including UNICEF, PAHO and USAID. In 2015 he worked for six weeks with a CDC team in the Ivory Coast focusing on that W. African country’s preparedness for possible introduction of Ebola Virus Disease (EVD), and in 2018, again as a CDC consultant, worked for a month in Guinea on a project to help that country strengthen its Integrated Disease -
Omegahat Packages for R
News The Newsletter of the R Project Volume 1/1, January 2001 Editorial by Kurt Hornik and Friedrich Leisch As all of R, R News is a volunteer project. The editorial board currently consists of the R core devel- Welcome to the first volume of R News, the newslet- opment team plus Bill Venables. We are very happy ter of the R project for statistical computing. R News that Bill—one of the authorities on programming the will feature short to medium length articles covering S language—has offered himself as editor of “Pro- topics that might be of interest to users or developers grammer’s Niche”, a regular column on R/S pro- of R, including gramming. This first volume already features a broad range Changes in R: new features of the latest release • of different articles, both from R core members and other developers in the R community (without Changes on CRAN: new add-on packages, • whom R would never have grown to what it is now). manuals, binary distributions, mirrors, . The success of R News critically depends on the ar- Add-on packages: short introductions to or re- ticles in it, hence we want to ask all of you to sub- • views of R extension packages mit to R News. There is no formal reviewing pro- cess yet, however articles will be reviewed by the ed- Programmer’s Niche: nifty hints for program- itorial board to ensure the quality of the newsletter. • ming in R (or S) Submissions should simply be sent to the editors by email, see the article on page 30 for details on how to Applications: Examples of analyzing data with • write articles. -
Gröbner Basis and Structural Equation Modeling by Min Lim a Thesis
Grobner¨ Basis and Structural Equation Modeling by Min Lim A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Statistics University of Toronto Copyright c 2010 by Min Lim Abstract Gr¨obnerBasis and Structural Equation Modeling Min Lim Doctor of Philosophy Graduate Department of Statistics University of Toronto 2010 Structural equation models are systems of simultaneous linear equations that are gener- alizations of linear regression, and have many applications in the social, behavioural and biological sciences. A serious barrier to applications is that it is easy to specify models for which the parameter vector is not identifiable from the distribution of the observable data, and it is often difficult to tell whether a model is identified or not. In this thesis, we study the most straightforward method to check for identification – solving a system of simultaneous equations. However, the calculations can easily get very complex. Gr¨obner basis is introduced to simplify the process. The main idea of checking identification is to solve a set of finitely many simultaneous equations, called identifying equations, which can be transformed into polynomials. If a unique solution is found, the model is identified. Gr¨obner basis reduces the polynomials into simpler forms making them easier to solve. Also, it allows us to investigate the model-induced constraints on the covariances, even when the model is not identified. With the explicit solution to the identifying equations, including the constraints on the covariances, we can (1) locate points in the parameter space where the model is not iden- tified, (2) find the maximum likelihood estimators, (3) study the effects of mis-specified models, (4) obtain a set of method of moments estimators, and (5) build customized parametric and distribution free tests, including inference for non-identified models. -
Sigmaplot 11: Now with Total Sigmastat Integration
SigmaPlot 11: Now with Total SigmaStat Integration Imagine my joy as I discovered a complete package of publication-quality graphics software with analytic and presentation tools John A. Wass, Ph.D., in: Scientific Computing International, Jan/Feb 2009 The SYSTAT people who market this product have thrown me a curve. For years, I have bemoaned the fact that most of the upgrade and development efforts that went into the SigmaPlot/SigmaStat software seemed to be biased to the plot side. When I observed that the new package was merely named SigmaPlot, and I further failed to find SigmaStat integration features (the stuff that connects the two programs), the Figure 1: SigmaPlot graphics and wizards, including the Quick Start natural conclusion seemed to be that the statistical Menu (upper right) and the graph program was jettisoned in favor of the graphics. wizard (bottom center) The above introductory narrative is intended to alert the reader to this editor’s long- time love affair with SigmaStat. It was the first statistical software that I used, (seemingly) the first to make a seamless transition from DOS to Windows, and the very first to offer that wonderful Wizard to we befuddled amateur statisticians. My introduction to SigmaPlot came much later, and use of that was only stimulated when the two became integrated. Later on, a pharmacology menu was added and the usage of the plotting software was greatly extended. Of course, the new version has added further graphics and helps to make an already useful program even easier to use. It is now a complete package of publication-quality graphics software with analytic and presentation tools. -
Kwame Nkrumah University of Science and Technology, Kumasi
KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, KUMASI, GHANA Assessing the Social Impacts of Illegal Gold Mining Activities at Dunkwa-On-Offin by Judith Selassie Garr (B.A, Social Science) A Thesis submitted to the Department of Building Technology, College of Art and Built Environment in partial fulfilment of the requirement for a degree of MASTER OF SCIENCE NOVEMBER, 2018 DECLARATION I hereby declare that this work is the result of my own original research and this thesis has neither in whole nor in part been prescribed by another degree elsewhere. References to other people’s work have been duly cited. STUDENT: JUDITH S. GARR (PG1150417) Signature: ........................................................... Date: .................................................................. Certified by SUPERVISOR: PROF. EDWARD BADU Signature: ........................................................... Date: ................................................................... Certified by THE HEAD OF DEPARTMENT: PROF. B. K. BAIDEN Signature: ........................................................... Date: ................................................................... i ABSTRACT Mining activities are undertaken in many parts of the world where mineral deposits are found. In developing nations such as Ghana, the activity is done both legally and illegally, often with very little or no supervision, hence much damage is done to the water bodies where the activities are carried out. This study sought to assess the social impacts of illegal gold mining activities at Dunkwa-On-Offin, the capital town of Upper Denkyira East Municipality in the Central Region of Ghana. The main objectives of the research are to identify factors that trigger illegal mining; to identify social effects of illegal gold mining activities on inhabitants of Dunkwa-on-Offin; and to suggest effective ways in curbing illegal mining activities. Based on the approach to data collection, this study adopts both the quantitative and qualitative approach. -
Full-Text (PDF)
Vol. 13(6), pp. 153-162, June 2019 DOI: 10.5897/AJPS2019.1785 Article Number: E69234960993 ISSN 1996-0824 Copyright © 2019 Author(s) retain the copyright of this article African Journal of Plant Science http://www.academicjournals.org/AJPS Full Length Research Paper Adaptability and yield stability of bread wheat (Triticum aestivum) varieties studied using GGE-biplot analysis in the highland environments of South-western Ethiopia Leta Tulu1* and Addishiwot Wondimu2 1National Agricultural Biotechnology Research Centre, P. O. Box 249, Holeta, Ethiopia. 2Department of Plant Sciences, College of Agriculture and Veterinary Science, Ambo University. P. O. Box 19, Ambo, Ethiopia. Received 13 February, 2019; Accepted 11 April, 2019 The objectives of this study were to evaluate released Ethiopian bread wheat varieties for yield stability using the GGE biplot method and identify well adapted and high-yielding genotypes for the highland environments of South-western Ethiopia. Twenty five varieties were evaluated in a randomized complete block design with three replications at Dedo and Gomma during the main cropping season of 2016 and at Dedo, Bedelle, Gomma and Manna during the main cropping season of 2017, generating a total of six environments in location-by-year combinations. Combined analyses of variance for grain yield indicated highly significant (p<0.001) mean squares due to environments, genotypes and genotype-by- environment interaction. Yield data were also analyzed using the GGE (that is, G, genotype + GEI, genotype-by-environment interaction) biplot method. Environment explained 73.2% of the total sum of squares, and genotype and genotype X environment interaction explained 7.16 and 15.8%, correspondingly. -
SQSTM1 Mutations in Familial and Sporadic Amyotrophic Lateral Sclerosis
ORIGINAL CONTRIBUTION SQSTM1 Mutations in Familial and Sporadic Amyotrophic Lateral Sclerosis Faisal Fecto, MD; Jianhua Yan, MD, PhD; S. Pavan Vemula; Erdong Liu, MD; Yi Yang, MS; Wenjie Chen, MD; Jian Guo Zheng, MD; Yong Shi, MD, PhD; Nailah Siddique, RN, MSN; Hasan Arrat, MD; Sandra Donkervoort, MS; Senda Ajroud-Driss, MD; Robert L. Sufit, MD; Scott L. Heller, MD; Han-Xiang Deng, MD, PhD; Teepu Siddique, MD Background: The SQSTM1 gene encodes p62, a major In silico analysis of variants was performed to predict al- pathologic protein involved in neurodegeneration. terations in p62 structure and function. Objective: To examine whether SQSTM1 mutations con- Results: We identified 10 novel SQSTM1 mutations (9 tribute to familial and sporadic amyotrophic lateral scle- heterozygous missense and 1 deletion) in 15 patients (6 rosis (ALS). with familial ALS and 9 with sporadic ALS). Predictive in silico analysis classified 8 of 9 missense variants as Design: Case-control study. pathogenic. Setting: Academic research. Conclusions: Using candidate gene identification based on prior biological knowledge and the functional pre- Patients: A cohort of 546 patients with familial diction of rare variants, we identified several novel (n=340) or sporadic (n=206) ALS seen at a major aca- SQSTM1 mutations in patients with ALS. Our findings demic referral center were screened for SQSTM1 muta- provide evidence of a direct genetic role for p62 in ALS tions. pathogenesis and suggest that regulation of protein deg- radation pathways may represent an important thera- Main Outcome Measures: We evaluated the distri- peutic target in motor neuron degeneration. bution of missense, deletion, silent, and intronic vari- ants in SQSTM1 among our cohort of patients with ALS. -
Software Developer
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