Exploring the multivariate structure of missing values using the R package VIM
|
|
|
- Moses Leonard
- 6 years ago
- Views:
Transcription
1 Exploring the multivariate structure of missing values using the R package VIM Matthias Templ 1,2, Andreas Alfons 1, Peter Filzmoser 1 1 Department of Statistics and Probability Theory, Vienna University of Technology 2 Department of Methodology, Statistics Austria Rennes, July 8, 2009 Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
2 Content 1 Motivation 2 Visualization of missing values 3 Conclusions Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
3 Missing values Motivation Real data sets often contain missing values: x x 1p. NA. X = NA,. NA. x n x np with n observations, p variables, and some missing values. (NA) Examples: nonresponse in surveys, element concentration below detection limit in chemical analyses. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
4 Motivation Comments on missing values Most statistical methods can only be applied to complete data. In order to select an appropriate imputation method (especially for model-based imputation), it is necessary to know the multivariate structure of the missing values beforehand. Visualizing missing values may not only help to detect the missing value mechanisms, but also to gain insight into the quality and various other aspects of the data. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
5 Motivation Missing value mechanisms Three important cases (e.g., Little and Rubin 2002): MCAR (Missing Completely At Random): P(X miss X) = P(X miss ) MAR (Missing At Random): P(X miss X) = P(X miss X obs ) MNAR (Missing Not At Random): P(X miss X) = P(X miss X obs, X miss ) where X = (X obs, X miss ) denotes the complete data, and X obs and X miss are the observed and missing parts, respectively. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
6 Visualization of missing values Visualization of missing values Famous books and almost all articles about missing values do not address vizualization. Visualization tools for missing values are rarely or not at all implemented in SAS, SPSS, STATA or even R. Through linking, missing values can be highlighted in GGobi (Cook and Swayne 2007) and Mondrian (Theus 2002). MANET (Unwin et al. 1996, Theus et al. 1997) is quite powerful, but only available for older Apple systems with PowerPC architecture and Mac OS. Visualization tools for missing values need to be available for the R community so that visualization of missing valuess, imputation and analysis can all be done from within R, without the need of additional software. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
7 Visualization of missing values Histogram and spinogram missing/observed in py010n age missing/observed in py010n age Figure: Austrian EU-SILC data from 2004 with missings generated in variable age. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
8 Visualization of missing values Marginplot py130n pek_n Figure: Austrian EU-SILC data from Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
9 Visualization of missing values Scatterplot matrix pek_n age py010n Figure: Austrian EU-SILC data from Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
10 Matrixplot Visualization of missing values P r py010n py035n py050n py090n py100n pek_n bundesld age Index Figure: Austrian EU-SILC data from Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
11 Visualization of missing values Parallel coordinate plot sex pek_g P P P P age bundesld Figure: Austrian EU-SILC data from 2004 Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
12 Visualization of missing values Parallel boxplots obs. in py010n miss. in py010n obs. in py035n miss. in py035n obs. in py050n miss. in py050n obs. in py070n miss. in py070n obs. in py080n miss. in py080n obs. in py090n miss. in py090n obs. in py100n miss. in py100n obs. in py110n miss. in py110n obs. in py130n miss. in py130n obs. in py140n miss. in py140n pek_n Figure: Austrian EU-SILC data from Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
13 Conclusions General Statements The detection of missing value mechanisms is quite complex when using models or tests. Statistical methods frequently lead to only vague statements about the missing value mechanisms. Non-robust methods lead to erroneous statements about missing value mechanisms for data containing outliers. Visualization tools are easier to handle and more powerful, but flexible, easy-to-use visualization software is required. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
14 Conclusions The R package VIM The R package VIM (Templ and Filzmoser 2008, Templ and Alfons 2009)... has all previously shown plots implemented, along with some more. is a tool for explorative data analysis of data with missing values. makes it possible to analyze the multivariate structure of missing values. comes with a graphical user interface (GUI). contains interactive features. allows producing high-quality graphics for publications. is available on CRAN ( Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
15 Conclusions Graphical user interface of the R Package VIM Figure: VIM GUI Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
16 Acknowledgments Conclusions This work was partly funded by the European Union (represented by the European Commission) within the 7 th framework programme for research (Theme 8, Socio-Economic Sciences and Humanities, Project AMELI (Advanced Methodology for European Laeken Indicators), Grant Agreement No ). Visit for more information. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
17 Conclusions References I D. Cook and D.F. Swayne. Interactive and Dynamic Graphics for Data Analysis: With R and GGobi. Springer, New York, ISBN R.J.A. Little and D.B. Rubin. Statistical Analysis with Missing Data. Wiley, New York, 2nd edition, ISBN M. Templ and A. Alfons. VIM: Visualization and Imputation of Missing Values, URL R package version 1.3. M. Templ and P. Filzmoser. Visualization of missing values using the R-package VIM. Research Report CS , Department of Statistics and Probability Theory, Vienna University of Technology, URL CS complete.pdf. Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
18 Conclusions References II M. Theus. Interactive data visualization using mondrian. Journal of Statistical Software, 7(11): 1 9, URL M. Theus, H. Hofmann, B. Siegl, and A. Unwin. MANET - Extensions to interactive statistical graphics for missing values. In In New Techniques and Technologies for Statistics II, pages IOS Press, A. Unwin, G. Hawkins, H. Hofmann, and B. Siegl. Interactive graphics for data sets with missing values: MANET. Journal of Computational and Graphical Statistics, 5(2): , Templ, Alfons, Filzmoser (TUW) Exploring the structure of missing values Rennes, July 8, / 18
BE540 - Introduction to Biostatistics Computer Illustration. Topic 1 Summarizing Data Software: STATA. A Visit to Yellowstone National Park, USA
BE540 - Introduction to Biostatistics Computer Illustration Topic 1 Summarizing Data Software: STATA A Visit to Yellowstone National Park, USA Source: Chatterjee, S; Handcock MS and Simonoff JS A Casebook
Policy Recommendations and Methodological Report
Advanced Methodology for European Laeken Indicators Deliverables 10.1 and 10.2 Policy Recommendations and Methodological Report Version: 2011 Ralf Münnich, Stefan Zins, Andreas Alfons, Christian Bruch,
PERMUTATION TESTS FOR COMPLEX DATA
PERMUTATION TESTS FOR COMPLEX DATA Theory, Applications and Software Fortunato Pesarin Luigi Salmaso University of Padua, Italy TECHNISCHE INFORMATIONSBiBUOTHEK UNIVERSITATSBIBLIOTHEK HANNOVER V WILEY
Use of administrative sources and registers in the Finnish EU-SILC survey
Use of administrative sources and registers in the Finnish EU-SILC survey Workshop on best practices for EU-SILC revision Marie Reijo, Senior Researcher Content Preconditions for good registers utilisation
Statistical Disclosure Control for Microdata
Statistical Disclosure Control for Microdata Matthias Templ Statistical Disclosure Control for Microdata Methods and Applications in R 123 Matthias Templ Institute of Data Analysis and Process Design (IDP)
Discussion of The power of monitoring: how to make the most of a contaminated multivariate sample
Stat Methods Appl https://doi.org/.7/s-7-- COMMENT Discussion of The power of monitoring: how to make the most of a contaminated multivariate sample Domenico Perrotta Francesca Torti Accepted: December
Building a more stable predictive logistic regression model. Anna Elizabeth Campain
Building a more stable predictive logistic regression model Anna Elizabeth Campain Common problems when working with clinical data Missing data Imbalanced class distribution Unstable logistic regression
Business Statistics. Lecture 2: Descriptive Statistical Graphs and Plots
Business Statistics Lecture 2: Descriptive Statistical Graphs and Plots 1 Goals for this Lecture Graphical descriptive statistics Histograms (and bar charts) Boxplots Scatterplots Time series plots Mosaic
SETTING FOOD SAFETY RISK ANALYSIS RESEARCH PRIORITIES FOR HORIZON EUROPE. Marta Hugas EFSA Chief Scientist
SETTING FOOD SAFETY RISK ANALYSIS RESEARCH PRIORITIES FOR HORIZON EUROPE Marta Hugas EFSA Chief Scientist 70 th Advisory Forum meeting Vienna, Austria, 28-29 November 2018 70 th Advisory Forum meeting
Brief Tutorial on the Statistical Top-Down PLC Channel Generator
Brief Tutorial on the Statistical Top-Down PLC Channel Generator Abstract Andrea M. Tonello Università di Udine - Via delle Scienze 208-33100 Udine - Italy web: www.diegm.uniud.it/tonello - email: tonello@uniud.it
Using Administrative Records for Imputation in the Decennial Census 1
Using Administrative Records for Imputation in the Decennial Census 1 James Farber, Deborah Wagner, and Dean Resnick U.S. Census Bureau James Farber, U.S. Census Bureau, Washington, DC 20233-9200 Keywords:
CS 889 Advanced Topics in Human- Computer Interaction. Experimental Methods in HCI
CS 889 Advanced Topics in Human- Computer Interaction Experimental Methods in HCI Overview A brief overview of HCI Experimental Methods overview Goals of this course Syllabus and course details HCI at
Curriculum Vitae. Professional Experience: Iowa State University appointment: Assistant Professor Statistics Jan present
Curriculum Vitae Heike Hofmann Department of Statistics Assistant Professor Degrees: Ph.D. Augsburg University (Germany) Statistics Dec. 2000 M.Sc. Augsburg University (Germany) Mathematics Feb. 1998 (minor
Why Should We Care? More importantly, it is easy to lie or deceive people with bad plots
Elementary Plots Why Should We Care? Everyone uses plotting But most people ignore or are unaware of simple principles Default plotting tools (or default settings) are not always the best More importantly,
How Many Imputations are Really Needed? Some Practical Clarifications of Multiple Imputation Theory
Prev Sci (2007) 8:206 213 DOI 10.1007/s11121-007-0070-9 How Many Imputations are Really Needed? Some Practical Clarifications of Multiple Imputation Theory John W. Graham & Allison E. Olchowski & Tamika
A Hybrid Risk Management Process for Interconnected Infrastructures
A Hybrid Management Process for Interconnected Infrastructures Stefan Schauer Workshop on Novel Approaches in and Security Management for Critical Infrastructures Vienna, 19.09.2017 Contents Motivation
Constructing a Toolkit to Evaluate Quality of State and Local Administrative Data
University of Pennsylvania ScholarlyCommons 2018 ADRF Network Research Conference Presentations ADRF Network Research Conference Presentations 11-2018 Constructing a Toolkit to Evaluate Quality of State
Multivariate Regression Techniques for Analyzing Auto- Crash Variables in Nigeria
ISSN 2224-386 (Paper) ISSN 2225-092 (Online) Vol., No., 20 Multivariate Regression Techniques for Analyzing Auto- Crash Variables in Nigeria Olushina Olawale Awe * Mumini Idowu Adarabioyo 2. Department
What are the chances?
What are the chances? Student Worksheet 7 8 9 10 11 12 TI-Nspire Investigation Student 90 min Introduction In probability, we often look at likelihood of events that are influenced by chance. Consider
Ace of diamonds. Graphing worksheet
Ace of diamonds Produce a screen displaying a the Ace of diamonds. 2006 Open University A silver-level, graphing challenge. Reference number SG1 Graphing worksheet Choose one of the following topics and
Results of Proficiency Test Free Formaldehyde in textile October 2011
Results of Proficiency Test Free Formaldehyde in textile October 2011 Organised by: Author: Correctors: Report: Spijkenisse, the Netherlands ing. L. Dijkstra dr. R. Visser & ing. N. Boelhouwer iis11a04
CS Game Programming, Fall 2014
CS 38101 Game Programming, Fall 2014 Recommended Text Learn Unity 4 for ios Game Development, Philip Chu, 2013, Apress, ISBN-13 (pbk): 978-1-4302-4875-0 ISBN-13 (electronic): 978-1-4302-4876-7, www.apress.com.
User-friendly Matlab tool for easy ADC testing
User-friendly Matlab tool for easy ADC testing Tamás Virosztek, István Kollár Budapest University of Technology and Economics, Department of Measurement and Information Systems Budapest, Hungary, H-1521,
Communication and dissemination strategy
Communication and dissemination strategy 2016-2020 Communication and dissemination strategy 2016 2020 Communication and dissemination strategy 2016-2020 Published by Statistics Denmark September 2016 Photo:
Austrian Work Plan for data collection in the fisheries and aquaculture sectors
GENERAL DIVISION AGRICULTURAL POLICY AND DATA MANAGEMENT Division II/1 Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management Council Regulation (EC) No 199/2008 of 25 February
Sampling Techniques. 70% of all women married 5 or more years have sex outside of their marriages.
Sampling Techniques Introduction In Women and Love: A Cultural Revolution in Progress (1987) Shere Hite obtained several impacting results: 84% of women are not satisfied emotionally with their relationships.
6. Multivariate EDA. ACE 492 SA - Spatial Analysis Fall 2003
1 Objectives 6. Multivariate EDA ACE 492 SA - Spatial Analysis Fall 2003 c 2003 by Luc Anselin, All Rights Reserved This lab covers some basic approaches to carry out EDA with a focus on discovering multivariate
6 Sampling. 6.2 Target population and sampling frame. See ECB (2013a), p. 80f. MONETARY POLICY & THE ECONOMY Q2/16 ADDENDUM 65
6 Sampling 6.1 Introduction The sampling design for the second wave of the HFCS in Austria was specifically developed by the OeNB in collaboration with the survey company IFES (Institut für empirische
Chapter 1 The Innovative Bakery Dialogue
Chapter 1 The Innovative Bakery Dialogue A methodology for SME bakeries to develop innovative sustainable products and services in a participatory process with their stakeholders Daniele Haiböck-Sinner
Analyzing Data Properties using Statistical Sampling Techniques
Analyzing Data Properties using Statistical Sampling Techniques Illustrated on Scientific File Formats and Compression Features Julian M. Kunkel kunkel@dkrz.de 2016-06-21 Outline 1 Introduction 2 Exploring
POLICY SIMULATION AND E-GOVERNANCE
POLICY SIMULATION AND E-GOVERNANCE Peter SONNTAGBAUER cellent AG Lassallestraße 7b, A-1020 Vienna, Austria Artis AIZSTRAUTS, Egils GINTERS, Dace AIZSTRAUTA Vidzeme University of Applied Sciences Cesu street
Data Integration Activities on the Way to the Dutch Virtual Census of 2011
Data Integration Activities on the Way to the Dutch Virtual Census of 2011 Eric Schulte Nordholt Statistics Netherlands Division Social and Spatial Statistics Department Support and Development Section
2011, Stat-Ease, Inc.
Practical Aspects of Algorithmic Design of Physical Experiments from an Engineer s perspective Pat Whitcomb Stat-Ease Ease, Inc. 612.746.2036 fax 612.746.2056 pat@statease.com www.statease.com Statistics
Building a common information architecture for the Commission. October 14, 2014
Building a common information architecture for the Commission October 14, 2014 Introduction: what we did last time Explained process of building a common architecture Explained card sorting scope and planning
Article. The Internet: A New Collection Method for the Census. by Anne-Marie Côté, Danielle Laroche
Component of Statistics Canada Catalogue no. 11-522-X Statistics Canada s International Symposium Series: Proceedings Article Symposium 2008: Data Collection: Challenges, Achievements and New Directions
Supplementary questionnaire on the 2011 Population and Housing Census SWITZERLAND
Supplementary questionnaire on the 2011 Population and Housing Census SWITZERLAND Supplementary questionnaire on the 2011 Population and Housing Census Fields marked with are mandatory. INTRODUCTION As
Investigation of noise and vibration impact on aircraft crew, studied in an aircraft simulator
The 33 rd International Congress and Exposition on Noise Control Engineering Investigation of noise and vibration impact on aircraft crew, studied in an aircraft simulator Volker Mellert, Ingo Baumann,
Statistics Laboratory 7
Pass the Pigs TM Statistics 104 - Laboratory 7 On last weeks lab we looked at probabilities associated with outcomes of the game Pass the Pigs TM. This week we will look at random variables associated
Organization of Data. Participant Workbook. The Quality Group - Revised 8/20/09 ORGANIZING DATA - My Notes. Participant Workbook
Organization of Data Participant Workbook The Quality Group - Revised 8/20/09 ORGANIZING DATA - The Quality Group, All Rights Reserved Ver. 5.1 ORGANIZING DATA - 1 The Quality Group. All Rights Reserved
Visual Data Mining of Remote Sensing Data
Visual Data Mining of Remote Sensing Data Jürgen Symanzik*, Utah State University, Logan, UT *e-mail: symanzik@sunfs sunfs.math..math.usu.edu WWW: http://www.math.usu usu.edu/~ /~symanzik with Louise Griffith,
LASER server: ancestry tracing with genotypes or sequence reads
LASER server: ancestry tracing with genotypes or sequence reads The LASER method Supplementary Data For each ancestry reference panel of N individuals, LASER applies principal components analysis (PCA)
Symmetric (Mean and Standard Deviation)
Summary: Unit 2 & 3 Distributions for Quantitative Data Topics covered in Module 2: How to calculate the Mean, Median, IQR Shapes of Histograms, Dotplots, Boxplots Know the difference between categorical
How can it be right when it feels so wrong? Outliers, diagnostics, non-constant variance
How can it be right when it feels so wrong? Outliers, diagnostics, non-constant variance D. Alex Hughes November 19, 2014 D. Alex Hughes Problems? November 19, 2014 1 / 61 1 Outliers Generally Residual
Use of forecasting for education & training: Experience from other countries
Use of forecasting for education & training: Experience from other countries Twinning-Project MK2007/IB/SO/02, MAZ III Lorenz Lassnigg (lassnigg@ihs.ac.at; www.equi.at) Input to EU-Twinning-project workshop
Social Innovation and new pathways to social changefirst insights from the global mapping
Social Innovation and new pathways to social changefirst insights from the global mapping Social Innovation2015: Pathways to Social change Vienna, November 18-19, 2015 Prof. Dr. Jürgen Howaldt/Antonius
Measuring the Performance of Smart Cities in Europe
Topic D: Practitioner-academic reports Neumann H-M. Pangerl E, Airaksinen M., Ahvenniemi H., Bosch P., DeCunto A., Homeier I., Huovila A., Jakutyte- Walangitang D. Jongeneel S., Kontinakis N., Kotakorpi
FastPass A Harmonized Modular Reference System for Automated Border Crossing (ABC)
FastPass A Harmonized Modular Reference System for Automated Border Crossing (ABC) EAB - Research Project Conference, Darmstadt, September 19 th, 2016 Presented by Markus Clabian Senior Research Engineer,
A-level History of Art
A-level History of Art HART2 Themes in History of Art Report on the Examination 2250 June 2013 Version: 1.0 Further copies of this Report are available from aqa.org.uk Copyright 2013 AQA and its licensors.
Strategy for the development of an African Science and Technology Policy framework
AFRICAN UNION Strategy for the development of an African Science and Technology Policy framework By Dr. Abdul-Hakim Rajab Elwaer Director of HRST AUC The Department of Human Resources Science and Technology
Multivariate Permutation Tests: With Applications in Biostatistics
Multivariate Permutation Tests: With Applications in Biostatistics Fortunato Pesarin University ofpadova, Italy JOHN WILEY & SONS, LTD Chichester New York Weinheim Brisbane Singapore Toronto Contents Preface
Growing an Organic Indoor Location System
Growing an Organic Indoor Location System Jun-geun Park MIT CSAIL Joint work with: Ben Charrow (MIT), Dorothy Curtis (MIT), Jonathan Battat (MIT), Einat Minkov (Nokia, Univ. of Haifa), Jamey Hicks (Nokia),
Monday, 1 December 2014
Monday, 1 December 2014 9:30 10:00 Welcome/opening remarks Introduction of the participants 10:00-11:00 Introduction to evaluation of census data Objectives of evaluation of census data, types and sources
LINK ADAPTATION IN GENERAL PACKET RADIO SERVICES (GPRS) Juan Li
LINK ADAPTATION IN GENERAL PACKET RADIO SERVICES (GPRS) Part II Juan Li, HUT 28th.Jan, 3 Link Adaptation in GPRS 1/27 Simulation Model ---One Example Figure 1 One example of link level model 28th.Jan,
Table 1. List of NFL divisions that have won the Superbowl over the past 52 years.
MA 2113 Homework #1 Table 1. List of NFL divisions that have won the Superbowl over the past 52 years. NFC North AFC West NFC East NFC North AFC South NFC North NFC East NFC East AFC West NFC East AFC
Measurement Systems Analysis
11 Measurement Systems Analysis Measurement Systems Analysis Overview, 11-2, 11-4 Gage Run Chart, 11-23 Gage Linearity and Accuracy Study, 11-27 MINITAB User s Guide 2 11-1 Chapter 11 Measurement Systems
PRICES OF THE LIBERTY STANDING QUARTER
This document deals with the prices paid by collectors for quarters in the Liberty standing set, issued between 1916 and 1930. Year / Mint / Type Mintage Value 1916 52,000 14,690 1917 Type 1 8,740,000
Urn Sampling Without Replacement: Enumerative Combinatorics In R
Urn Sampling Without Replacement: Enumerative Combinatorics In R Robin K. S. Hankin Auckland University of Technology Abstract This vignette is based on Hankin (2007). This short paper introduces a code
SAMPLE. This chapter deals with the construction and interpretation of box plots. At the end of this chapter you should be able to:
find the upper and lower extremes, the median, and the upper and lower quartiles for sets of numerical data calculate the range and interquartile range compare the relative merits of range and interquartile
Package SvyNom. February 24, 2015
Package SvyNom February 24, 2015 Type Package Title Nomograms for Right-Censored Outcomes from Survey Designs Version 1.1 Date 2015-01-06 Author Mithat Gonen, Marinela Capanu Maintainer Mithat Gonen
NEW ASSOCIATION IN BIO-S-POLYMER PROCESS
NEW ASSOCIATION IN BIO-S-POLYMER PROCESS Long Flory School of Business, Virginia Commonwealth University Snead Hall, 31 W. Main Street, Richmond, VA 23284 ABSTRACT Small firms generally do not use designed
Environmental Accounting - Communication and quality improvement
Sacha Baud Directorate Spatial Statistics 24 April 2013 Environmental Accounting - Communication and quality improvement DIMESA Workshop www.statistik.at We provide information Content Short overview on
Synchronization between a SystemC based offline Restbus Simulator and a HIL FlexRay network
Synchronization between a SystemC based offline Restbus Simulator and a HIL FlexRay network Gilles Bertrand Defo, Wolfgang Mueller University of Paderborn / C-LAB Fürstenallee 11 33102 Paderborn Germany
Section 1.5 Graphs and Describing Distributions
Section 1.5 Graphs and Describing Distributions Data can be displayed using graphs. Some of the most common graphs used in statistics are: Bar graph Pie Chart Dot plot Histogram Stem and leaf plot Box
Research Development Request - Profile Template. European Commission
Research Development Request - Profile Template European Commission Research Development Request Profile The following table can be used as a template for drafting a Research Development Request profile.
New societal challenges for the European Union New challenges for social sciences and the humanities
EUROPEAN COMMISSION European Research Area Social sciences & humanities New societal challenges for the European Union New challenges for social sciences and the humanities Thinking across boundaries Modernising
Overview. Scotland s Census. Development of methods. What did we do about it? QA panels. Quality assurance and dealing with nonresponse
Overview Scotland s Census Quality assurance and dealing with nonresponse in the Census Quality assurance approach Documentation of quality assurance The Estimation System in Census and its Accuracy Cecilia
Uncertainty in CT Metrology: Visualizations for Exploration and Analysis of Geometric Tolerances
Uncertainty in CT Metrology: Visualizations for Exploration and Analysis of Geometric Tolerances Artem Amirkhanov 1, Bernhard Fröhler 1, Michael Reiter 1, Johann Kastner 1, M. Eduard Grӧller 2, Christoph
United Nations Educational, Scientific and Cultural Organization (UNESCO)
Goal 9: Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial
Adjusting for linkage errors to analyse coverage of the Integrated Data Infrastructure (IDI) and the administrative population (IDI-ERP)
Adjusting for linkage errors to analyse coverage of the Integrated Data Infrastructure (IDI) and the administrative population (IDI-ERP) Hochang Choi, Statistical Analyst, Stats NZ Paper prepared for the
Why Should We Care? Everyone uses plotting But most people ignore or are unaware of simple principles Default plotting tools are not always the best
Elementary Plots Why Should We Care? Everyone uses plotting But most people ignore or are unaware of simple principles Default plotting tools are not always the best More importantly, it is easy to lie
Use of DOE Methodology for Investigating Factors that Influence the Operating Time of the Eton Grundig FR-200 Emergency Radio
Engineering 9516 Similitude, Modelling and Data Analysis Memorial University of Newfoundland January April 2009 Term Paper Use of DOE Methodology for Investigating Factors that Influence the Operating
Applying a Logic Model Framework to Mineral Processing Education
A ROADMAP FOR MINERALS PROCESSING EDUCATION Applying a Logic Model Framework to Mineral IMPC Education Commission Study Update LOIS FINCH PHD JAMES FINCH PHD DIANA DRINKWATER Summary The objective of the
Close the gender pay gap.
Close the gender pay gap Summary What is the gender pay gap? Why does the gender pay gap persist? What action has the EU taken? Why does it matter? The gender pay gap across the lifecycle What can be done?
Methodology Statement: 2011 Australian Census Demographic Variables
Methodology Statement: 2011 Australian Census Demographic Variables Author: MapData Services Pty Ltd Version: 1.0 Last modified: 2/12/2014 Contents Introduction 3 Statistical Geography 3 Included Data
Health Informatics Basics
Health Informatics Basics Foundational Curriculum: Cluster 4: Informatics Module 7: The Informatics Process and Principles of Health Informatics Unit 1: Health Informatics Basics 20/60 Curriculum Developers:
ENUMERATE: Measuring the progress of digital heritage in Europe
ENUMERATE: Measuring the progress of digital heritage in Europe Marco de Niet (DEN Foundation, NL) Unesco WSIS+10 Review meeting Paris, 26 February 2013 Why should we collect statistics on digitisation
Convolutional Coding Using Booth Algorithm For Application in Wireless Communication
Available online at www.interscience.in Convolutional Coding Using Booth Algorithm For Application in Wireless Communication Sishir Kalita, Parismita Gogoi & Kandarpa Kumar Sarma Department of Electronics
LAB MANUAL EXPERIMENT NO. 9
LAB MANUAL EXPERIMENT NO. 9 Aim of the Experiment: 1. Measure the characteristics of a Directional Coupler. 2. Use of the Directional Coupler and Ratio Meter to construct a Scalar Network Analyzer for
Fostering Innovative Ideas and Accelerating them into the Market
Fostering Innovative Ideas and Accelerating them into the Market Dr. Mikel SORLI 1, Dr. Dragan STOKIC 2, Ana CAMPOS 2, Antonio SANZ 3 and Miguel A. LAGOS 1 1 Labein, Cta. de Olabeaga, 16; 48030 Bilbao;
Evaluation of the gender pay gap in Lithuania
Distr.: General 3 May 2016 English Economic Commission for Europe Conference of European Statisticians Work Session on Gender Statistics Vilnius, Lithuania 1-3 June 2016 Item 5 of the provisional agenda
Data users and data producers interaction: the Web-COSI project experience
ESS Modernisation Workshop 16-17 March 2016 Bucharest www.webcosi.eu Data users and data producers interaction: the Web-COSI project experience Donatella Fazio, Istat Head of Unit R&D Projects Web-COSI
Sample Surveys. Chapter 11
Sample Surveys Chapter 11 Objectives Population Sample Sample survey Bias Randomization Sample size Census Parameter Statistic Simple random sample Sampling frame Stratified random sample Cluster sample
EUROPEAN COMMISSION DIRECTORATE-GENERAL ENVIRONMENT Directorate D - Water, Chemicals & Biotechnology ENV.D.2 - Marine
EUROPEAN COMMISSION DIRECTORATE-GENERAL ENVIRONMENT Directorate D - Water, Chemicals & Biotechnology ENV.D.2 - Marine Document MSCG November 20 MARINE STRATEGY FRAMEWORK DIRECTIVE COMMON IMPLEMENTATION
A Closest Fit Approach to Missing Attribute Values in Data Mining
A Closest Fit Approach to Missing Attribute Values in Data Mining Sanjay Gaur and M.S. Dulawat Department of Mathematics and Statistics, Maharana Bhupal Campus Mohanlal Sukhadia University, Udaipur, INDIA
Chapter 12 Summary Sample Surveys
Chapter 12 Summary Sample Surveys What have we learned? A representative sample can offer us important insights about populations. o It s the size of the same, not its fraction of the larger population,
Lesson Sampling Distribution of Differences of Two Proportions
STATWAY STUDENT HANDOUT STUDENT NAME DATE INTRODUCTION The GPS software company, TeleNav, recently commissioned a study on proportions of people who text while they drive. The study suggests that there
1 st Joint JRC-IIASA Summer School EVIDENCE & POLICY
1 st Joint JRC-IIASA Summer School EVIDENCE & POLICY Wednesday 2 nd Friday 4 th September 2015 at IIASA, Laxenburg/Vienna, Austria (Version: 31 August 2015) Page 2 of 47 Programme Tuesday 1 st September
A4BLUE - Adaptive Automation in Assembly For BLUE collar workers satisfaction in Evolvable context
A4BLUE Newsletter Issue n 2 September 2017 Updates on the first year project results A4BLUE PROJECT- Adaptive Automation in Assembly For BLUE collar workers satisfaction in Evolvable context Enjoy reading
Audio Imputation Using the Non-negative Hidden Markov Model
Audio Imputation Using the Non-negative Hidden Markov Model Jinyu Han 1,, Gautham J. Mysore 2, and Bryan Pardo 1 1 EECS Department, Northwestern University 2 Advanced Technology Labs, Adobe Systems Inc.
MODERN CENSUS IN POLAND
United Nations International Seminar on Population and Housing Censuses: Beyond the 2010 Round 27-29 November 2012 Seoul, Republic of Korea SESSION 7: Use of modern technologies for censuses MODERN CENSUS
Vincent Thomas Mule, Jr., U.S. Census Bureau, Washington, DC
Paper SDA-06 Vincent Thomas Mule, Jr., U.S. Census Bureau, Washington, DC ABSTRACT As part of the evaluation of the 2010 Census, the U.S. Census Bureau conducts the Census Coverage Measurement (CCM) Survey.
page 2 / 5
MIXED EFFECTS MODELS FOR COMPLEX DATA CHAPMAN HALL CRC MONOGRAPHS ON STATISTICS APPLIED PROBABILITY APPLIED STATISTICS PROBABILITY 5E B W WITH WILEYPLUS SET page 1 / 5 page 2 / 5 mixed effects models for
Armenian Experience on Agricultural Census
Armenian Experience on Agricultural Census Name(s) of the Author(s): Mr. Stepan Mnatsakanyan, Ms. Anahit Safyan* Address (es) of the Author(s): Ms. Anahit Safyan Institution, Department: National Statistical
Sample size, sample weights in household surveys
Sample size, sample weights in household surveys Outline Background Total quality in surveys Sampling Controversy Sample size, stratification and clustering effects An overview of the quality dimensions
Publishing date: 23/07/2015 Document title: We appreciate your feedback. Share this document
Publishing date: 23/07/2015 Document title: We appreciate your feedback Please click on the icon to take a 5 online survey and provide your feedback about this document Share this document REPORT ON UNIT
GUIDELINES SOCIAL SCIENCES AND HUMANITIES RESEARCH MATTERS. ON HOW TO SUCCESSFULLY DESIGN, AND IMPLEMENT, MISSION-ORIENTED RESEARCH PROGRAMMES
SOCIAL SCIENCES AND HUMANITIES RESEARCH MATTERS. GUIDELINES ON HOW TO SUCCESSFULLY DESIGN, AND IMPLEMENT, MISSION-ORIENTED RESEARCH PROGRAMMES to impact from SSH research 2 INSOCIAL SCIENCES AND HUMANITIES
Descriptive Statistics II. Graphical summary of the distribution of a numerical variable. Boxplot
MAT 2379 (Spring 2012) Descriptive Statistics II Graphical summary of the distribution of a numerical variable We will present two types of graphs that can be used to describe the distribution of a numerical
Call for contributions
Call for contributions FTA 1 2018 - Future in the Making F u t u r e - o r i e n t e d T e c h n o l o g y A n a l y s i s Are you developing new tools and frames to understand and experience the future?
VisuaLax: Visually Relaxing Augmented Reality Application Using Music and Visual Therapy
DOI: 10.7763/IPEDR. 2013. V63. 5 VisuaLax: Visually Relaxing Augmented Reality Application Using Music and Visual Therapy Jeremiah Francisco +, Benilda Eleonor Comendador, Angelito Concepcion Jr., Ron
Mobilisation and Mutual Learning (MML) Action Plans on Societal Challenges
KI-NA-24-837-EN-C E U R O P E A N COMMISSION Research & Innovation Science in Society You are a research organisation, a business or a civil society organisation ready to collaborate with other actors