Statistical Assistants

Total Page:16

File Type:pdf, Size:1020Kb

Statistical Assistants Operations Research Analysts Statistical Assistants TORQ Analysis of Operations Research Analysts to Statistical Assistants INPUT SECTION: Transfer Title O*NET Filters Operations Research Importance LeveL: Weight: From Title: 15-2031.00 Abilities: Analysts 50 1 Importance LeveL: Weight: To Title: Statistical Assistants 43-9111.00 Skills: 69 1 Labor Market Weight: Maine Statewide Knowledge: Importance Level: 69 Area: 1 OUTPUT SECTION: Grand TORQ: 85 Ability TORQ Skills TORQ Knowledge TORQ Level Level Level 90 82 82 Gaps To Narrow if Possible Upgrade These Skills Knowledge to Add Ability Level Gap Impt Skill Level Gap Impt Knowledge Level Gap Impt Finger No Skills Upgrade Required! No Knowledge Upgrades Required! 37 14 50 Dexterity Perceptual 37 9 56 Speed Speech 48 6 65 Recognition Near Vision 57 4 72 Speech Clarity 48 2 65 Selective 44 2 62 Attention Visualization 37 2 50 LEVEL and IMPT (IMPORTANCE) refer to the Target Statistical Assistants. GAP refers to level difference between Operations Research Analysts and Statistical Assistants. ASK ANALYSIS Ability Level Comparison - Abilities with importance scores over 50 Operations Research Description Analysts Statistical Assistants Importance Mathematical Reasoning 67 67 90 Number Facility 66 64 84 Oral Comprehension 72 64 59 Near Vision 53 57 72 TORQ Analysis Page 1 of 11. Copyright 2009. Workforce Associates, Inc. Operations Research Analysts Statistical Assistants Written Comprehension 65 64 53 Oral Expression 65 64 57 Information Ordering 51 65 55 Category Flexibility 51 65 57 Speech Recognition 42 48 65 Speech Clarity 46 48 65 Written Expression 62 62 53 Deductive Reasoning 62 62 55 Inductive Reasoning 48 62 60 Selective Attention 42 44 62 Problem Sensitivity 44 56 57 Flexibility of Closure 51 42 56 Perceptual Speed 28 37 56 Fluency of Ideas 50 53 60 Originality 44 53 57 Visualization 35 37 50 Finger Dexterity 23 37 50 Skill Level Comparison - Abilities with importance scores over 69 Operations Research Description Analysts Statistical Assistants Importance Reading Comprehension 86 72 94 Critical Thinking 82 70 89 Mathematics 91 72 86 Active Listening 76 67 85 Time Management 59 59 83 Complex Problem 73 Solving 85 68 Quality Control Analysis 63 72 59 Active Learning 71 80 70 Speaking 71 69 61 Knowledge Level Comparison - Knowledge with importance scores over 69 Description Operations Research Analysts Statistical Assistants Importance TORQ Analysis Page 2 of 11. Copyright 2009. Workforce Associates, Inc. Operations Research Analysts Statistical Assistants Mathematics 93 73 82 Computers and Electronics 73 67 73 Experience & Education Comparison Related Work Experience Comparison Required Education Level Comparison Statistical Operations Description Operations Research Analysts Assistants Description Research Statistical Analysts Assistants 10+ years 0% 0% Doctoral 12% 0% 8-10 years 0% 0% Professional Degree 0% 0% 6-8 years 4% 0% Post-Masters Cert 0% 0% 4-6 years 8% 14% 2-4 years 29% 13% Master's Degree 18% 70% 1-2 years 8% 23% Post-Bachelor Cert 0% 0% 6-12 8% 27% 16% 43% months Bachelors 3-6 months 0% 12% AA or Equiv 0% 12% 1-3 months 0% 0% Some College 0% 15% 0-1 month 0% 0% Post-Secondary 0% 8% Certificate None 41% 8% High Scool Diploma 0% 2% or GED No HSD or GED 0% 0% Operations Research Analysts Statistical Assistants Most Common Educational/Training Requirement: Master's degree Moderate-term on-the-job training Job Zone Comparison 5 - Job Zone Five: Extensive Preparation Needed 3 - Job Zone Three: Medium Preparation Needed Extensive skill, knowledge, and experience are needed for Previous work-related skill, knowledge, or experience is these occupations. Many require more than five years of required for these occupations. For example, an electrician experience. For example, surgeons must complete four must have completed three or four years of apprenticeship years of college and an additional five to seven years of or several years of vocational training, and often must have specialized medical training to be able to do their job. passed a licensing exam, in order to perform the job. A bachelor's degree is the minimum formal education required for these occupations. However, many also require Most occupations in this zone require training in vocational graduate school. For example, they may require a master's schools, related on-the-job experience, or an associate's degree, and some require a Ph.D., M.D., or J.D. (law degree. Some may require a bachelor's degree. degree). Employees may need some on-the-job training, but most of Employees in these occupations usually need one or two these occupations assume that the person will already have years of training involving both on-the-job experience and the required skills, knowledge, work-related experience, informal training with experienced workers. and/or training. Tasks Operations Research Analysts Statistical Assistants Core Tasks Core Tasks Generalized Work Activities: Generalized Work Activities: Analyzing Data or Information - Interacting With Computers - Using Identifying the underlying principles, computers and computer systems reasons, or facts of information by (including hardware and software) to breaking down information or data into program, write software, set up separate parts. functions, enter data, or process Interacting With Computers - Using information. TORQ Analysis Page 3 of 11. Copyright 2009. Workforce Associates, Inc. Operations Research Analysts Statistical Assistants computers and computer systems Processing Information - Compiling, (including hardware and software) to coding, categorizing, calculating, program, write software, set up tabulating, auditing, or verifying functions, enter data, or process information or data. information. Getting Information - Observing, Making Decisions and Solving Problems - receiving, and otherwise obtaining Analyzing information and evaluating information from all relevant sources. results to choose the best solution and Communicating with Supervisors, Peers, solve problems. or Subordinates - Providing information to Getting Information - Observing, supervisors, co-workers, and subordinates receiving, and otherwise obtaining by telephone, in written form, e-mail, or information from all relevant sources. in person. Processing Information - Compiling, Analyzing Data or Information - coding, categorizing, calculating, Identifying the underlying principles, tabulating, auditing, or verifying reasons, or facts of information by information or data. breaking down information or data into separate parts. Specific Tasks Specific Tasks Occupation Specific Tasks: Occupation Specific Tasks: Analyze information obtained from management in order to conceptualize Check source data in order to verify its and define operational problems. completeness and accuracy. Break systems into their component Check survey responses for errors such as parts, assign numerical values to each the use of pens instead of pencils, and component, and examine the set aside response forms that cannot be mathematical relationships between them. used. Collaborate with others in the Code data as necessary prior to computer organization to ensure successful entry, using lists of codes. implementation of chosen problem Compile reports, charts, and graphs that solutions. describe and interpret findings of analyses. Collaborate with senior managers and Compile statistics from source materials, decision-makers to identify and solve a such as production and sales records, variety of problems, and to clarify quality-control and test records, time management objectives. sheets, and survey sheets. Define data requirements; then gather Compute and analyze data, using and validate information, applying statistical formulas and computers or judgment and statistical tests. calculators. Design, conduct, and evaluate Discuss data presentation requirements experimental operational models in cases with clients. where models cannot be developed from existing data. Enter data into computers for use in analyses and reports. Develop and apply time and cost networks in order to plan, control, and File data and related information, and review large projects. maintain and update databases. Develop business methods and Interview people and keep track of their procedures, including accounting systems, responses. file systems, office systems, logistics Organize paperwork such as survey forms systems, and production schedules. and reports for distribution and for Formulate mathematical or simulation analysis. models of problems, relating constants Participate in the publication of data and and variables, restrictions, alternatives, information. conflicting objectives, and their numerical parameters. Select statistical tests for analyzing data. Observe the current system in operation, Send out surveys. and gather and analyze information about each of the parts of component problems, Detailed Tasks using a variety of sources. Detailed Work Activities: Perform validation and testing of models to ensure adequacy; reformulate models assist with business or managerial as necessary. research Prepare management reports defining collect scientific or technical data and evaluating problems and collect statistical data recommending solutions. compile numerical or statistical data Specify manipulative or computational TORQ Analysis Page 4 of 11. Copyright 2009. Workforce Associates, Inc. Operations Research Analysts Statistical Assistants methods to be applied to models. create mathematical or statistical diagrams or charts Study
Recommended publications
  • 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.
    [Show full text]
  • Catalogo Generale ADALTA N. 25
    SOFTWARE PER L’INNOVAZIONE SOFTWARE Catalogo Generale catalogo completo su: www.adalta.it www.adalta.it L’innovazione tecnologica è fondamentale per le aziende e le istituzioni italiane per essere più competitive. Adalta propone e supporta in Italia l’utilizzo di alcuni tra i più importanti software al mondo per l’innovazione tecnologica, la ricerca e lo sviluppo. Durante più di 20 anni di attività, Adalta ha selezionato nel proprio catalogo i migliori software disponibili, che sono divenuti lo standard mondiale nei diversi settori di applicazione. Centinaia di aziende private, istituzioni pubbliche, università italiane si avvalgono dei servizi di grandissima qualità offerti da Adalta: supporto nell’individuare il prodotto più adatto alle specifi che esigenze, consulenza e formazione per sfruttare al meglio le potenzialità del software. I clienti Adalta vengono costantemente aggiornati grazie alle newsletter tecnico scientifi che ricche di utili informazioni, che vengono pubblicate e rese disponibili per la consultazione gratuita sul sito. Supporto Pre-Vendita Adalta Notizie » www.adalta.it/Contatti » www.adalta.it/AdaltaNotizie Contattaci telefonicamente o via email ti aiuteremo a identi- Informazioni utili, novità, applicazioni per utilizzare al meglio i fi care il software più adatto al tuo lavoro e a determinare la software distribuiti da Adalta. Viene inviata una breve email miglior tipologia di licenza in base alla tue esigenze. con il sommario delle notizie pubblicate. Supporto Post-Vendita Consulenza e Corsi di Formazione » www.adalta.it/Supporto » www.adalta.it/Consulenza Adalta è rivenditore autorizzato e importatore diretto per l’Ita- Adalta aiuta costantemente i tecnici e i professionisti a cono- lia di tutti i prodotti a catalogo.
    [Show full text]
  • Software for Food Engineering Applications - Bon, J
    FOOD ENGINEERING – Vol. IV - Software for Food Engineering Applications - Bon, J. SOFTWARE FOR FOOD ENGINEERING APPLICATIONS Bon, J. Department of Food Technology, Polytechnic University of Valencia,Spain Keywords: Food engineering, software, software sources, engineering software, units operations. Contents 1. Introduction 2. Software Sources 3. Software Tools 3.1. General Software 3.2. Food Physical Properties 3.3. Process Simulation and Design 3.4. Control 3.5. Other 3.6. On-Line Executable Software 4. Conclusions Glossary Bibliography Biographical Sketch Summary Currently, there are industry standard flowsheeting and design programs available, which are widely used by chemical engineers. However, existing programs for food processing applications are limited in their ability to handle the wide variety of processes and products encountered in the food industry. The scientific impediments involved consist of a lack of knowledge of relationships between physicochemical and sensory properties, complexity of food components, their chemical/biomedical behavior, and intricacy of on-line measurement of product properties. A main problem lies in the fact that most of the changes are irreversible. The food engineer deals with computers in one of two ways: 1) understanding how to use commercialUNESCO software that usually perf–orms EOLSS well and has a forthcoming interface making it user-friendly and 2) understanding how to develop software that can solve specific problems,SAMPLE because many calculations CHAPTERSfound in one’s professional career will be unique. Nowadays, a great deal of more or less general-purpose software exists that could be useful in Food Engineering, the main drawback in most cases being the calculation of physical properties.
    [Show full text]
  • List of New Applications Added in ARL #2586
    List of new applications added in ARL #2586 Application Name Publisher NetCmdlets 2016 /n software 1099 Pro 2009 Corporate 1099 Pro 1099 Pro 2020 Enterprise 1099 Pro 1099 Pro 2008 Corporate 1099 Pro 1E Client 5.1 1E SyncBackPro 9.1 2BrightSparks FindOnClick 2.5 2BrightSparks TaxAct 2002 Standard 2nd Story Software Phone System 15.5 3CX Phone System 16.0 3CX 3CXPhone 16.3 3CX Grouper Plus System 2021 3M CoDeSys OPC Server 3.1 3S-Smart Software Solutions 4D 15.0 4D Duplicate Killer 3.4 4Team Disk Drill 4.1 508 Software NotesHolder 2.3 Pro A!K Research Labs LibraryView 1.0 AB Sciex MetabolitePilot 2.0 AB Sciex Advanced Find and Replace 5.2 Abacre Color Picker 2.0 ACA Systems Password Recovery Toolkit 8.2 AccessData Forensic Toolkit 6.0 AccessData Forensic Toolkit 7.0 AccessData Forensic Toolkit 6.3 AccessData Barcode Xpress 7.0 AccuSoft ImageGear 17.2 AccuSoft ImagXpress 13.6 AccuSoft PrizmDoc Server 13.1 AccuSoft PrizmDoc Server 12.3 AccuSoft ACDSee 2.2 ACD Systems ACDSync 1.1 ACD Systems Ace Utilities 6.3 Acelogix Software True Image for Crucial 23. Acronis Acrosync 1.6 Acrosync Zen Client 5.10 Actian Windows Forms Controls 16.1 Actipro Software Opus Composition Server 7.0 ActiveDocs Network Component 4.6 ActiveXperts Multiple Monitors 8.3 Actual Tools Multiple Monitors 8.8 Actual Tools ACUCOBOL-GT 5.2 Acucorp ACUCOBOL-GT 8.0 Acucorp TransMac 12.1 Acute Systems Ultimate Suite for Microsoft Excel 13.2 Add-in Express Ultimate Suite for Microsoft Excel 21.1 Business Add-in Express Ultimate Suite for Microsoft Excel 21.1 Personal Add-in Express
    [Show full text]
  • Simulation Study to Compare the Random Data Generation from Bernoulli Distribution in Popular Statistical Packages
    Simulation Study to Compare the Random Data Generation from Bernoulli Distribution in Popular Statistical Packages Manash Pratim Kashyap Department of Business Administration Assam University, Silchar, India [email protected] Nadeem Shafique Butt PIQC Institute of Quality Lahore, Pakistan [email protected] Dibyojyoti Bhattacharjee Department of Business Administration Assam University, Silchar, India [email protected] Abstract In study of the statistical packages, simulation from probability distributions is one of the important aspects. This paper is based on simulation study from Bernoulli distribution conducted by various popular statistical packages like R, SAS, Minitab, MS Excel and PASW. The accuracy of generated random data is tested through Chi-Square goodness of fit test. This simulation study based on 8685000 random numbers and 27000 tests of significance shows that ability to simulate random data from Bernoulli distribution is best in SAS and is closely followed by R Language, while Minitab showed the worst performance among compared packages. Keywords: Bernoulli distribution, Goodness of Fit, Minitab, MS Excel, PASW, SAS, Simulation, R language 1. Introduction Use of Statistical software is increasing day by day in scientific research, market surveys and educational research. It is therefore necessary to compare the ability and accuracy of different statistical softwares. This study focuses a comparison of random data generation from Bernoulli distribution among five softwares R, SAS, Minitab, MS Excel and PASW (Formerly SPSS). The statistical packages are selected for comparison on the basis of their popularity and wide usage. Simulation is the statistical method to recreate situation, often repeatedly, so that likelihood of various outcomes can be more accurately estimated.
    [Show full text]
  • A Bibliography of the American Statistician
    A Bibliography of The American Statistician Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 30 March 2018 Version 1.30 Title word cross-reference [BM01, Ber81, BHO00, Box81, Bro10, CA97, DG97, Eis79, GJLW05, Gro90, HJM08, KG90, LaM94, LD98, MC91, Zuo10]. U [Sch91, Len83]. X [Spi87, Spi86]. x (X <X <X ) [HL96]. :338 [Fre07c]. :833 2 1 2 k [Sch93a]. x jx [Sch93a]. Y [Spi87, Spi86]. Z [Fre07c]. 1: m [Lev97]. 1 × 1 × r [Dun03]. 2k 2 1 [BHO00, Eis79, HJM08, Shi88b]. [SM79]. 2 × 2 [Che11, MW92, MH93, SVR11, Kra88]. 2 × k -Distance [All97]. -Means [Tar07]. [GK99]. 5 [Bar02, Len01c]. -statistics [KD87]. -tables [Lau65]. -Test −X t (n − 1)(s=fng) [Zuo10]. α [HB03]. α [Bro10]. -Value [BS11]. -Values [MTA08]. χ2 [SP85]. ED100p [CCW+86]. F [Chr03, Gue79, Lau65, LD98, ML92, Pei93, 1.4 [Cow04c]. 11 [Hil05d]. 11th [Mil03]. 12 PS98c, Sho03, ZPM+11, SM79, FK86]. f 0=f [Hil03c]. 12.0 [vH04]. 12.01 [Hil04b]. 12.2 [JH83]. gh [HR06]. H [Bet00]. I [Pav88]. k 0 [Hil08f]. 14th [RvE97]. 1913-1994 [CR95]. [BP02, Tar07]. L [Hos92]. L1 [All97]. n 1919 [Ben93]. 19th [LR06]. 1st [Mil03]. [BHO00, Kah87]. O [KD87]. ⊗ [Hu07]. P [BS11, Don99, MTA08, SSC99, Sch96a, 2g [Won98]. 2.0 [Maa99]. 2000 Ber96a, BH02, Bro10, HB03, MW92, Rya09, [ESL09, WJM+03]. 21st [McD99].
    [Show full text]
  • Full Curriculum Vitae (PDF)
    Mohamed Rahouti, P.HD. Candidate Department of Electrical Engineering, University of South Florida 4202 E. Fowler Ave, CMC 303C, Tampa, FL 33620-5399, USA Phone: (813) 315-0306, Email: [email protected] Website: http://mrahouti.myweb.usf.edu/ LinkedIn: https://www.linkedin.com/in/mohamed-rahouti-936347124/ Education Ph.D., University of South Florida, Tampa, Florida, USA, January 2017-April 2020 • Doctoral degree candidate in Electrical Engineering, Supervisors Drs. Kaiqi Xiong and Nasir Ghani • Courses in cyber security, computer networking and security, applied cryptography, machine learning, artificial intelligence, data mining, advanced databases, graph theory, optimization and queueing theory (GPA > 3.7 out of 4) Masters, University of South Florida, Tampa, Florida, USA, January 2015-December 2016 • Masters degree in Mathematics, Statistics concentration, Supervisor Prof. Kaiqi Xiong • Courses in mathematics, probability theory, applied statistics, data mining and advanced data science, engineering mathematics (GPA >3.5 out of 4) Bachelors, Ecole Supérieure d'Ingénierie En Sciences Appliquées, Morocco, Sept. 2009–Aug. 2013 • Bachelors degree in Computer Engineering • Courses in communications, advanced programing, data structures, algorithm theory, networks, and software engineering (GPA >17 out of 20) Technical Skills • Data Science and analytics: • Matlab, SPSS, Minitab, Microsoft Excel, Tableau, R/RStudio, Stata, SigmaStat, Izenda, Sisense, Sales Force Analytics Cloud. • Machine learning and data mining: • Matlab, TensorFlow, Octave, Weka, Google Cloud Platform, R, H2O, Deeplearning4j, Scikit- learn, XGBoost, PyTorch, Torch, RapidMiner • Software Engineering & Programming Languages: • Python, C/C++/C#, Java, Assembler, bash, Perl, Ruby, Rust, iOS/Swift • JEE: Struts, Spring, Hibernate, RMI, EJB. • .Net: VB.NET, Windows Forms, Windows Presentation Foundation, MVC2, JavaServerFaces, JavaServerPages.
    [Show full text]
  • "R Coding and Modeling" In: the Encyclopedia of Archaeological
    for many other programs where these details R Coding and Modeling are not available to the user (cf. PAST, and all BEN MARWICK commercial software). Second, for many archae- University of Washington, USA ologists a spreadsheet program such as Microsoft Excel is their primary tool of data analysis and visualization. The primary mode of interaction is by manipulating cells in the spreadsheet, and Introduction through mouse-clicks to access commands in thedrop-downmenus.Rdiffersfromallother R is a programming language and computing statistical software because it is not a spreadsheet environment useful for statistical and geospatial program and has very few mouse-driven actions. analysis, data visualization, and mapping. It is Instead, R has a prompt to which typed com- significant as the most widely used scientific pro- mands are interactively sent to the R interpreter. gramming language in archaeology. This entry As a programming language, R gives the user will briefly describe the origins of R and survey greatflexibilitythroughaccesstoavastvarietyof its distinctive features, including how it enables methods. The user is not limited to built-in func- reproducible research. It will also highlight some tions, but can easily create new ones. The R inter- current uses of R in archaeology, and suggest some possible future directions. preterevaluatescommandstypedbytheuser,and R was originally developed in New Zealand in the computed output is printed to the screen or the early 1990s as an academic research project to stored for later use. These typed commands are create a language for introductory data analysis saved in a plain-text R script file, which becomes courses. It is closely related to the S language and arecordofallthestepsinadataanalysis.
    [Show full text]
  • Volume XXVII Number 2 2015 ITALIAN JOURNAL of FOOD SCIENCE (RIVISTA ITALIANA DI SCIENZA DEGLI ALIMENTI) 2Nd Series
    ISSN 1120-1770 Volume XXVII Number 2 2015 ITALIAN JOURNAL OF FOOD SCIENCE (RIVISTA ITALIANA DI SCIENZA DEGLI ALIMENTI) 2nd series Founded By Paolo Fantozzi under the aeges of the University of Perugia Official Journal of the Italian Society of Food Science and Technology Società Italiana di Scienze e Tecnologie Alimentari (S.I.S.T.Al) Initially supported in part by the Italian Research Council (CNR) - Rome - Italy Recognised as a “Journal of High Cultural Level” by the Ministry of Cultural Heritage - Rome - Italy Editor-in-Chief: Paolo Fantozzi - Dipartimento di Scienze Economico-Estimative e degli Alimenti, Università di Perugia, S. Costanzo, I-06126 Perugia, Italy - Tel. +39 075 5857910 - Telefax +39 075 5857939-5857943 - e-mail: [email protected] Co-Editors: Gallina Toschi Tullia - Alma Mater Studiorum - Università di Bologna, e-mail: [email protected] Mannino Saverio - Università degli Studi di Milano, e-mail: [email protected] Pittia Paola - Università degli Studi di Teramo, e-mail: [email protected] Pompei Carlo - Università degli Studi di Milano, e-mail: [email protected] Rolle Luca - Università degli Studi di Torino, e-mail: [email protected] Sinigaglia Milena - SIMTREA - Università degli Studi di Foggia, e-mail: [email protected] Publisher: Alberto Chiriotti - Chiriotti Editori srl, Viale Rimembranza 60, I-10064 Pinerolo, Italy - Tel. +39 0121 393127 - Fax +39 0121 794480 e-mail: [email protected] - URL: www.chiriottieditori.it Aim: The Italian Journal of Food Science is an international journal publishing original, basic and applied papers, reviews, short communications, surveys and opinions on food science and technology with specific reference to the Mediterranean Region.
    [Show full text]
  • Porcelain & Ceramic Products (B2B Procurement)
    Porcelain & Ceramic Products (B2B Procurement) Purchasing World Report Since 1979 www.datagroup.org Porcelain & Ceramic Products (B2B Procurement) Porcelain & Ceramic Products (B2B Procurement) 2 B B Purchasing World Report Porcelain & Ceramic Products (B2B Procurement) The Purchasing World Report is an extract of the main database and provides a number of limited datasets for each of the countries covered. For users needing more information, detailed data on Porcelain & Ceramic Products (B2B Procurement) is available in several Editions and Database versions. Users can order (at a discount) any other Editions, or the Database versions, as required from the After-Sales Service or from any Dealer. This research provides data the Buying of Materials, Products and Services used for Porcelain & Ceramic Products. Contents B2B Purchasing World Report ................................................................................................................................... 2 B2B Purchasing World Report Specifications ............................................................................................................ 4 Materials, Products and Services Purchased : US$ ........................................................................................... 4 Report Description .................................................................................................................................................. 6 Tables ....................................................................................................................................................................
    [Show full text]
  • Handbook of Knowledge Society Foresight
    European Foundation for the Improvement of Living and Working Conditions Handbook of Knowledge Society Foresight Executive summary Introduction Foresight in the knowledge society Main methods and issues Approaches to forecasting Generating strategic intelligence Scenarios in knowledge society foresight Planning and action Evaluating outcomes Concluding remarks Annexes: Annex A, Annex B, Annex C For full Contents click here This handbook is available in electronic format only Wyattville Road, Loughlinstown, Dublin 18, Ireland. - Tel: (+353 1) 204 31 00 - Fax: 282 42 09 / 282 64 56 e-mail: [email protected] - website: www.eurofound.eu.int Contents Executive summary 1. Introduction 1.1 Who and what is this handbook for? 1.2 What is the structure of the handbook? 1.3 What additional resources are available? 2. Foresight in the knowledge society 2.0 Introduction 2.1 The knowledge society 2.2 Foresight 3. Main methods and issues 3.0 Introduction 3.1 What are the main decisions to be made about a foresight exercise? 3.2 How will the focus of knowledge society foresight be determined? 3.3 How can the areas that require attention be identified? 3.4 What is the most suitable time horizon? 3.5 Who will pay and how long will it take? 3.6 What methods can be used to identify relevant expertise and stakeholders? 3.7 What methods can be used for raising awareness and building support? 3.8 What are the typical approaches for organising and managing foresight activities? 4. Approaches to forecasting 4.0 Introduction: the use of forecasting methods in knowledge society foresight 4.1 Forecasting approaches mainly based on expert judgement 4.2 Forecasting approaches mainly based on statistical or mathematical analysis 5.
    [Show full text]
  • Sigmastat® 4.0
    A d v i s o r y S t a t i s t i c s f o r S c i e n t i s t S i g m a S t a t 4 . 0 s SigmaStat® 4.0 L et an e xp e rt g u ide your r e s e a r c h a n a l y s i s S i g m a S t a t s o f t w a r e h e lp s you ever y step of the way D e s i g n e d by Scientists, f o r S c i e n t i s t s S i g m a S t a t 4 . 0 D e s i g n e d by Scientists, f o r S c i e n t i s t s S i g m a S t a t 4 . 0 SigmaStat Helps You Analyze Data Confidently, Visualize Results Easily SigmaStat is an easy-to-use, wizard-based statistical software package designed to guide users through every step of the analysis and perform powerful statistical analysis without being a statistical expert. SigmaStat is tailored to the areas of life science and medical research, but can be a valuable product to scientists in many fields. With SigmaStat, you can be confident that you have analyzed your data correctly. And you save time, too! Because it takes you step by step through the analysis, SigmaStat ensures that you: • Use the proper statistical method to analyze your data • Avoid the risk of statistical error • Interpret the results correctly • Generate an appropriate display and a professional report Features that make analysis fast and easy You don't need to know which statistical test is right for your data.
    [Show full text]