Sampling: What you don t know can hurt you. Juan Muñoz
|
|
- Stephanie Webb
- 5 years ago
- Views:
Transcription
1 Sampling: What you don t know can hurt you Juan Muñoz
2 Probability sampling Also known as Scientific Sampling. Households are selected randomly. Each household in the population has a known, nonzero probability of being included in the sample.
3 Basic Sampling Techniques The three basic techniques of probability sampling: Simple Random Sampling Multi-stage Sampling Stratified Sampling Most household surveys use a combination of these three techniques.
4 Probability sampling Permits establishing sampling errors and confidence intervals. Other sampling procedures (purposive sampling, convenience sampling, quota sampling, etc.) cannot do that. Other sampling procedures can also yield biased conclusions.
5 Simple Random Sampling Households are selected independently. Every household in the population has an equal chance or probability of being selected in the sample. This probability is: p = n/n where n=the size of the sample. N=the size of the study population.
6 Simple Random Sampling Simple random sampling is almost never the only technique used in practice, because: A Sampling Frame may not be available, or it would be very large (a Sampling Frame is a list of all units in a study population that can be used to select a sample from. Fieldwork may be difficult since the selected households would be too scattered.
7 Simple Random Sampling Simple random sampling is almost never the only technique used in practice, but it is useful to illustrate some basic facts about sampling: Sampling errors and confidence intervals. The relationship between sampling error and sample size. The relationship between sampling error and population size. Sampling errors vs. non-sampling errors.
8 Sampling error and sample size Sampling error e when estimating a proportion p with a sample of size n taken from an infinite population e = p( 1 p) n
9 Confidence intervals In a sample of 1,000 enterprises, 280 enterprises (28 percent) have been harassed by a predatory agency e = = ,000 Sampling error is 1.42 percent.
10 Confidence intervals In a sample of 1,000 enterprises, 280 enterprises (28 percent) have been harassed by a predatory agency. Sampling error is 1.42 percent. Sampling error percent confidence interval:28 ± percent confidence interval: 28 ±
11 Sampling error and sample size Sampling error To halve sampling error......sample size must be quadrupled Sample size
12 Sample size and population size Sampling error e when estimating a proportion p with a sample of size n taken from a population of size N e = 1 n N p( 1 p) n finite population correction
13 Sample size and population size Sample size needed for a given precision Population size
14 Sampling vs. non-sampling errors Error Total error Non-sampling error Sampling error Sample size
15 Two-stage Sampling The population is divided up into subgroups, or Primary Sampling Units (PSUs), that represent aggregates of individual households. In the first stage, a sample of PSUs is selected. In the second stage, a sample of individual households is chosen in each of the selected PSUs.
16 Two-stage Sampling Solves the problems of Simple Random Sampling Provides an opportunity to link community-level factors to household behavior The sample can be made self-weighted if In the first stage, PSUs are selected with Probability Proportional to Size (PPS) In the second stage, a fixed number of households are chosen within the selected PSUs The price to pay is cluster effect
17 Cluster effect Sampling error grows when the sample of size n is drawn from k PSUs, with m households in each PSU (n=k m) Intra-cluster correlation coefficient e 2 = e 2 [ 1+ ρ( m 1)] corrected Cluster effect
18 Cluster effects For a total sample size of 12,000 households Number of PSUs Number of households per PSU Intra-cluster correlation coefficient
19 Cluster effects For a total sample size of 12,000 households Number of PSUs Number of households per PSU Intra-cluster correlation coefficient
20 Cluster effects For a total sample size of 12,000 households Number of PSUs Number of households per PSU Intra-cluster correlation coefficient
21 Cluster effects For a total sample size of 12,000 households Number of PSUs Number of households per PSU Intra-cluster correlation coefficient ,
22 Stratified Sampling The population is divided up into subgroups or strata. A separate sample of households is then selected from each strata.
23 Stratified Sampling There are two primary reasons for using a stratified sampling design: To potentially reduce sampling error by gaining greater control over the composition of the sample. To ensure that particular groups within a population are adequately represented in the sample. The two objectives are generally contradictory in practice.
24 Stratified Sampling Stratification Variable: variable or variables by which a study population is divided up into strata (or groups) in order to select a stratified sample. Proportionate Stratified Sample: Stratified sample where the number of households selected from each strata is proportional to the number of units in each strata in the population. Disproportionate Stratified Sample: Stratified sample where the number of households selected from each strata is not proportional to the number of units in each strata in the population. Almost all national household surveys use Disproportionate Stratified Sampling. This implies that raising factors, or sampling weights need to be used to obtain national estimates from the sample.
25 Excluded strata Parts of the country may need to be excluded from the sample for security or other reasons
26 Measuring change Pros and cons of panel samples A panel can measure change more accurately A panel permits correlating change in the outcomes with change in other factors A panel approach may reduce the effort of the second and subsequent rounds Panels are harder to manage and entail longterm commitments between data users and producers Panels are subject to attrition (respondent fatigue, migration, disappearance from the market, etc.) A panel is more vulnerable to manipulation from the predatory agencies
27 Assuring good field work Juan Muñoz
28 What happens when fieldwork is poor? A long and frustrating process of data cleaning becomes unavoidable The data loose their policy-making relevance Data quality is not guaranteed The process converges (at best) to databases that are internally consistent The process entails a myriad of decisions, generally undocumented Users mistrust the data
29 Key factors Manage the survey as an integrated project Implement the team concept in the organization of field operations Integrate computer-based quality controls to field operations Establish strong supervision procedures Ensure sufficient training Work with a reduced staff over an extended period of data collection
30 Management levels Core staff Survey manager Field operations manager Data manager Tactical options for the organization of field teams Mobile teams with fixed data entry Mobile teams with integrated data entry Sometime in the future: the paperless interview
31 Mobile teams with fixed data entry Cote d Ivoire (1984) Peru (1985) Ghana Pakistan Guinea-Conakry Mozambique
32 Composition of a field team Supervisor Interviewers Data entry operator
33 The team and its tools Supervisor Interviewers Antropometrist Data entry operator
34 Alama Two PSUs visited in a fourweek period Bamako Regional Office
35 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
36 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
37 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
38 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
39 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
40 First week Alama Bamako Regional Office They complete first half of questionnaires in all selected households Operator remains in Regional Office Rest of the team travels to Alama
41 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
42 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama
43 First week Alama Bamako Regional Office Operator remains in Regional Office Rest of the team travels to Alama and back
44 First week Alama Bamako Regional Office Supervisor gives Alama questionnaires to DEO Rest of the team travels to Alama and back
45 Second week Alama Bamako Regional Office Operator enters first week data from Alama Rest of the team travels to Bamako
46 Second week Alama Bamako Regional Office Operator enters first week data from Alama Rest of the team travels to Bamako
47 Second week Alama Bamako Regional Office Operator enters first week data from Alama Rest of the team travels to Bamako They complete first half of questionnaires in all selected households
48 Second week Alama Bamako Regional Office Operator enters first week data from Alama Rest of the team travels to Bamako and back
49 Second week Alama Bamako Regional Office Rest of the team travels to Bamako and back Supervisor gives Bamako questionnaires to DEO. DEO gives back Alama questionnaires with flagged inconsistencies
50 Third week Alama Bamako Regional Office Team completes second half of questionnaires. They correct inconsistencies from first half Operator enters first week data from Bamako
51 Fourth week Alama Bamako Regional Office Operator enters second week data from Alama. Corrects inconsistencies from first round Team completes second half of questionnaires. They correct inconsistencies from first half
52 Fourth week The result is a clean data set on diskette, ready for analysis immediately after data collection Regional Office
53 Mobile teams with integrated data entry Nepal (1992) Argentina Paraguay Bangladesh (2000)
54 Mobile teams with integrated data entry Bamako Alama Team works with portable computers and printers Cocody Regional Office
55 Mobile teams with integrated data entry Bamako Alama Operator travels with the rest of the field team Cocody Regional Office
56 Mobile teams with integrated data entry Bamako Alama Cocody Data entry and validation almost immediate Regional Office
57 Mobile teams with integrated data entry Bamako Alama Cocody Reduced trips to and from Regional Office to selected PSUs Regional Office
58 Mobile teams with integrated data entry Bamako Alama Cocody Regional Office
59 Benefits of integration Provides reliable and timely databases Provides immediate feedback on the performance of the field staff, allowing early detection of inadequate behaviors Ensures that all field staff applies uniform criteria throughout the full period of data collection Solves inconsistencies through direct verification of households reality, rather that through office guesswork Is consistent with the total quality culture
60 Supervision tasks Verification of questionnaires for completeness Random re-interviews of households Observation of interviews
61 Selecting and training field staff Why is it important How long does it take How is it organized
62 Example: Day 2 of interviewer training Definition of household (and dwelling, family, etc.) Pictorial of a sample household Slide with an empty roster (explain case conventions, encoding, skip patterns, etc.) Fill the roster for the sample household (need for legible handwriting, recording of ages, use of a calendar of events, etc.) Role playing (trainer as a respondent, simulating borderline cases) Role playing (trainees interview each other)
Centre for Economic Policy Research
The Australian National University Centre for Economic Policy Research DISCUSSION PAPER The Reliability of Matches in the 2002-2004 Vietnam Household Living Standards Survey Panel Brian McCaig DISCUSSION
More information3rd takes a long time/costly difficult to ensure whole population surveyed cannot be used if the measurement process destroys the item
1a Observation or measurement of every member of a population. 1.2 2nd 1b Two from: 1.2 3rd takes a long time/costly difficult to ensure whole population surveyed cannot be used if the measurement process
More informationReliability. What We Will Cover. What Is It? An estimate of the consistency of a test score.
Reliability 4/8/2003 PSY 721 Reliability 1 What We Will Cover What reliability is. How a test s reliability is estimated. How to interpret and use reliability estimates. How to enhance reliability. 4/8/2003
More informationPPM Panels: A Guidebook for Arbitron Authorized Users
. Inc n ro bit lsen. r, A ie 13 of N 0 2 t 0/ par 3 9/ me On beca PPM Panels: A Guidebook for Arbitron Authorized Users PPM Panels: A Guidebook for Arbitron Authorized Users 2 Introduction In any given
More informationBARB Establishment Survey Annual Data Report: Volume 1 Total Network and Appendices
BARB Establishment Survey Annual Data Report: Volume 1 Total Network and Appendices Apr 2017 to Mar 2018 BARB ESTABLISHMENT SURVEY OF TV HOMES Page 1 DATA PERIOD: ANNUAL Apr 2017 - Mar 2018 Contents Page
More informationModeling memory for melodies
Modeling memory for melodies Daniel Müllensiefen 1 and Christian Hennig 2 1 Musikwissenschaftliches Institut, Universität Hamburg, 20354 Hamburg, Germany 2 Department of Statistical Science, University
More informationBARB Establishment Survey Quarterly Data Report: Total Network
BARB Establishment Survey Quarterly Data Report: Total Network Jan 2018 to Mar 2018 BARB ESTABLISHMENT SURVEY OF TV HOMES DATA PERIOD: QUARTERLY Jan - Mar 2018 Page 1 Contents Page Total Network (All Areas)
More informationSample Design and Weighting Procedures for the BiH STEP Employer Survey. David J. Megill Sampling Consultant, World Bank May 2017
Sample Design and Weighting Procedures for the BiH STEP Employer Survey David J. Megill Sampling Consultant, World Bank May 2017 1. Sample Design for BiH STEP Employer Survey The sampling frame for the
More informationBefore the Federal Communications Commission Washington, D.C ) ) ) ) ) ) ) ) ) REPORT ON CABLE INDUSTRY PRICES
Before the Federal Communications Commission Washington, D.C. 20554 In the Matter of Implementation of Section 3 of the Cable Television Consumer Protection and Competition Act of 1992 Statistical Report
More informationAP Statistics Sec 5.1: An Exercise in Sampling: The Corn Field
AP Statistics Sec.: An Exercise in Sampling: The Corn Field Name: A farmer has planted a new field for corn. It is a rectangular plot of land with a river that runs along the right side of the field. The
More informationexpressed on operational issues are those of the authors and not necessarily those of the U.S. Census Bureau.
Quality Control of Data Entry for the American Community Survey and the Impact of Errors on Data Quality 1 Andre Williams, Dale Garrett and Rita Petroni Andre Williams, U.S. Bureau of the Census, Washington,
More informationWHAT MAKES FOR A HIT POP SONG? WHAT MAKES FOR A POP SONG?
WHAT MAKES FOR A HIT POP SONG? WHAT MAKES FOR A POP SONG? NICHOLAS BORG AND GEORGE HOKKANEN Abstract. The possibility of a hit song prediction algorithm is both academically interesting and industry motivated.
More informationComparative Study of Electoral Systems (CSES) Module 3: Sample Design and Data Collection Report June 05, 2006
Comparative Study of Electoral Systems 1 Comparative Study of Electoral Systems (CSES) Module 3: Sample Design and Data Collection Report June 05, 2006 Country: Netherlands Date of Election: 9 June 2010
More informationQuantitative methods
Quantitative methods Week #7 Gergely Daróczi Corvinus University of Budapest, Hungary 23 March 2012 Outline 1 Sample-bias 2 Sampling theory 3 Probability sampling Simple Random Sampling Stratified Sampling
More informationSTAT 113: Statistics and Society Ellen Gundlach, Purdue University. (Chapters refer to Moore and Notz, Statistics: Concepts and Controversies, 8e)
STAT 113: Statistics and Society Ellen Gundlach, Purdue University (Chapters refer to Moore and Notz, Statistics: Concepts and Controversies, 8e) Learning Objectives for Exam 1: Unit 1, Part 1: Population
More informationHow Large a Sample? CHAPTER 24. Issues in determining sample size
388 Resampling: The New Statistics CHAPTER 24 How Large a Sample? Issues in Determining Sample Size Some Practical Examples Step-Wise Sample-Size Determination Summary Issues in determining sample size
More informationSampling Plans. Sampling Plan - Variable Physical Unit Sample. Sampling Application. Sampling Approach. Universe and Frame Information
Sampling Plan - Variable Physical Unit Sample Sampling Application AUDIT TYPE: REVIEW AREA: SAMPLING OBJECTIVE: Sampling Approach Type of Sampling: Why Used? Check All That Apply: Confidence Level: Desired
More informationA Parametric Autoregressive Model for the Extraction of Electric Network Frequency Fluctuations in Audio Forensic Authentication
Journal of Energy and Power Engineering 10 (2016) 504-512 doi: 10.17265/1934-8975/2016.08.007 D DAVID PUBLISHING A Parametric Autoregressive Model for the Extraction of Electric Network Frequency Fluctuations
More informationThe Relationship Between Movie theater Attendance and Streaming Behavior. Survey Findings. December 2018
The Relationship Between Movie theater Attendance and Streaming Behavior Survey Findings Overview I. About this study II. III. IV. Movie theater attendance and streaming consumption Quadrant Analysis:
More informationA Parametric Autoregressive Model for the Extraction of Electric Network Frequency Fluctuations in Audio Forensic Authentication
Proceedings of the 3 rd International Conference on Control, Dynamic Systems, and Robotics (CDSR 16) Ottawa, Canada May 9 10, 2016 Paper No. 110 DOI: 10.11159/cdsr16.110 A Parametric Autoregressive Model
More informationTutorial 0: Uncertainty in Power and Sample Size Estimation. Acknowledgements:
Tutorial 0: Uncertainty in Power and Sample Size Estimation Anna E. Barón, Keith E. Muller, Sarah M. Kreidler, and Deborah H. Glueck Acknowledgements: The project was supported in large part by the National
More informationComparison of Mixed-Effects Model, Pattern-Mixture Model, and Selection Model in Estimating Treatment Effect Using PRO Data in Clinical Trials
Comparison of Mixed-Effects Model, Pattern-Mixture Model, and Selection Model in Estimating Treatment Effect Using PRO Data in Clinical Trials Xiaolei Zhou, 1,2 Jianmin Wang, 1 Jessica Zhang, 1 Hongtu
More informationEXECUTIVE REPORT. All Media Survey 2012 (2)
EXECUTIVE REPORT Market Research Services Ltd. All Media Survey 2012 (2) Contact Details: Market Research Services Ltd. 16 Cargill Avenue Kingston 10. Tele: 929-6311 or 929-6349 Fax: 960-7753 Email: mrsl@flowja.com
More informationMost Canadians think the Prime Minister s trip to India was not a success
Most Canadians think the Prime Minister s trip to India was not a success National survey released March, 2018 Project 2018-1190c Summary More than three quarters of Canadians say that the Prime Minister
More informationObjective: Write on the goal/objective sheet and give a before class rating. Determine the types of graphs appropriate for specific data.
Objective: Write on the goal/objective sheet and give a before class rating. Determine the types of graphs appropriate for specific data. Khan Academy test Tuesday Sept th. NO CALCULATORS allowed. Not
More informationSampling Worksheet: Rolling Down the River
Sampling Worksheet: Rolling Down the River Name: Part I A farmer has just cleared a new field for corn. It is a unique plot of land in that a river runs along one side. The corn looks good in some areas
More informationCore ICT indicators on access to, and use of, ICTs by households and individuals
How to establish an ICT Indicator database in Indonesia 29 October 2 November 2007 Jakarta, Indonesia Core ICT indicators on access to, and use of, ICTs by households and individuals Esperanza C. Magpantay
More informationChapter 27. Inferences for Regression. Remembering Regression. An Example: Body Fat and Waist Size. Remembering Regression (cont.)
Chapter 27 Inferences for Regression Copyright 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 27-1 Copyright 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley An
More informationThe Proportion of NUC Pre-56 Titles Represented in OCLC WorldCat
The Proportion of NUC Pre-56 Titles Represented in OCLC WorldCat Jeffrey Beall and Karen Kafadar This article describes a research project that included a designed experiment and statistical analysis to
More informationAUDIOVISUAL COMMUNICATION
AUDIOVISUAL COMMUNICATION Laboratory Session: Recommendation ITU-T H.261 Fernando Pereira The objective of this lab session about Recommendation ITU-T H.261 is to get the students familiar with many aspects
More informationTowards a Stratified Learning Approach to Predict Future Citation Counts
Towards a Stratified Learning Approach to Predict Future Citation Counts Tanmoy Chakraborty Google India PhD Fellow IIT Kharagpur, India Suhansanu Kumar, Pawan Goyal, Niloy Ganguly, Animesh Mukherjee Dept.
More informationThe Urbana Free Library Patron Survey. Final Report
The Urbana Free Library Patron Survey Final Report CIRSS Center for Informatics Research in Science and Scholarship Graduate School of Library and Information Science University of Illinois at Urbana-Champaign
More informationNAA ENHANCING THE QUALITY OF MARKING PROJECT: THE EFFECT OF SAMPLE SIZE ON INCREASED PRECISION IN DETECTING ERRANT MARKING
NAA ENHANCING THE QUALITY OF MARKING PROJECT: THE EFFECT OF SAMPLE SIZE ON INCREASED PRECISION IN DETECTING ERRANT MARKING Mudhaffar Al-Bayatti and Ben Jones February 00 This report was commissioned by
More informationBuilding Trust in Online Rating Systems through Signal Modeling
Building Trust in Online Rating Systems through Signal Modeling Presenter: Yan Sun Yafei Yang, Yan Sun, Ren Jin, and Qing Yang High Performance Computing Lab University of Rhode Island Online Feedback-based
More informationIndia Peoplemeter Update VII
India Peoplemeter Update VII TAM - India Peoplemeter Update, v 1.1 August, 2008 Page 0 of 11 I. Introduction It may surprise many when we say that this is the third year of digital television data for
More informationSignal Survey Summary. submitted by Nanos to Signal Leadership Communication Inc., July 2018 (Submission )
A majority of Canadians want CEOs to communicate on social media during a crisis more than half feel that it should be done through the PR team with journalists Signal Survey Summary submitted by Nanos
More informationA year later, Trudeau remains near post election high on perceptions of having the qualities of a good political leader
A year later, Trudeau remains near post election high on perceptions of having the qualities of a good political leader Nanos Weekly Tracking ending November 18 th, 2016 (released November 22 nd, 2016-6
More informationMATH 214 (NOTES) Math 214 Al Nosedal. Department of Mathematics Indiana University of Pennsylvania. MATH 214 (NOTES) p. 1/11
MATH 214 (NOTES) Math 214 Al Nosedal Department of Mathematics Indiana University of Pennsylvania MATH 214 (NOTES) p. 1/11 CHAPTER 6 CONTINUOUS PROBABILITY DISTRIBUTIONS MATH 214 (NOTES) p. 2/11 Simple
More informationCanadians opinions on our connection to the monarchy
Canadians opinions on our connection to the monarchy National survey released May, 2016 Project 2016-831A > Support strong for keeping connection with monarchy Canadians feel it has had a positive impact
More informationLesson 7: Measuring Variability for Skewed Distributions (Interquartile Range)
: Measuring Variability for Skewed Distributions (Interquartile Range) Student Outcomes Students explain why a median is a better description of a typical value for a skewed distribution. Students calculate
More informationCopyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and
Copyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only. The thesis may not be reproduced elsewhere
More informationSUBMISSION AND GUIDELINES
SUBMISSION AND GUIDELINES Submission Papers published in the IABPAD refereed journals are based on a double-blind peer-review process. Articles will be checked for originality using Unicheck plagiarism
More informationCOMP Test on Psychology 320 Check on Mastery of Prerequisites
COMP Test on Psychology 320 Check on Mastery of Prerequisites This test is designed to provide you and your instructor with information on your mastery of the basic content of Psychology 320. The results
More informationPartisanship and the Media: Personal Politics Affect Where People Go, What They Trust, and Whether They Pay
Partisanship and the Media: Personal Politics Affect Where People Go, What They Trust, and Whether They Pay Conducted by the Media Insight Project An initiative of the American Press Institute and The
More informationBER margin of COM 3dB
BER margin of COM 3dB Yasuo Hidaka Fujitsu Laboratories of America, Inc. September 9, 2015 IEEE P802.3by 25 Gb/s Ethernet Task Force Abstract I was curious how much actual margin we have with COM 3dB So,
More informationCONCLUSION The annual increase for optical scanner cost may be due partly to inflation and partly to special demands by the State.
Report on a Survey of Changes in Total Annual Expenditures for Florida Counties Before and After Purchase of Touch Screens and A Comparison of Total Annual Expenditures for Touch Screens and Optical Scanners.
More informationunbiased , is zero. Yï) + iab Fuller and Burmeister [4] suggested the estimator: N =Na +Nb + Nab Na +NB =Nb +NA.
RELTIVE EFFICIENCY OF SOME TWO -FRME ESTIMTORS H. Huang, Minnesota State Department of Education 1. Introduction In sample surveys, a complete frame is often unavailable or too expensive to construct.
More informationThe Relationship Between Movie Theatre Attendance and Streaming Behavior. Survey insights. April 24, 2018
The Relationship Between Movie Theatre Attendance and Streaming Behavior Survey insights April 24, 2018 Overview I. About this study II. III. IV. Movie theatre attendance and streaming consumption Quadrant
More informationAP Statistics Sampling. Sampling Exercise (adapted from a document from the NCSSM Leadership Institute, July 2000).
AP Statistics Sampling Name Sampling Exercise (adapted from a document from the NCSSM Leadership Institute, July 2000). Problem: A farmer has just cleared a field for corn that can be divided into 100
More informationbwresearch.com twitter.com/bw_research facebook.com/bwresearch
2725 JEFFERSON STREET, SUITE 13, CARLSBAD CA 92008 50 MILL POND DRIVE, WRENTHAM, MA 02093 T (760) 730-9325 F (888) 457-9598 bwresearch.com twitter.com/bw_research facebook.com/bwresearch TABLE OF CONTENTS
More informationMID-TERM EXAMINATION IN DATA MODELS AND DECISION MAKING 22:960:575
MID-TERM EXAMINATION IN DATA MODELS AND DECISION MAKING 22:960:575 Instructions: Fall 2017 1. Complete and submit by email to TA and cc me, your answers by 11:00 PM today. 2. Provide a single Excel workbook
More informationMinimax Disappointment Video Broadcasting
Minimax Disappointment Video Broadcasting DSP Seminar Spring 2001 Leiming R. Qian and Douglas L. Jones http://www.ifp.uiuc.edu/ lqian Seminar Outline 1. Motivation and Introduction 2. Background Knowledge
More informationSoftware Engineering 2DA4. Slides 9: Asynchronous Sequential Circuits
Software Engineering 2DA4 Slides 9: Asynchronous Sequential Circuits Dr. Ryan Leduc Department of Computing and Software McMaster University Material based on S. Brown and Z. Vranesic, Fundamentals of
More informationConfidence Intervals for Radio Ratings Estimators
Social Statistics Section JSM 009 Confidence Intervals for Radio Ratings Estimators Richard Griffiths 1 1 Arbitron, Inc., 9705 Patuxent Woods Drive, Columbia, MD 1046 Abstract Arbitron s current method
More informationProcessor time 9 Used memory 9. Lost video frames 11 Storage buffer 11 Received rate 11
Processor time 9 Used memory 9 Lost video frames 11 Storage buffer 11 Received rate 11 2 3 After you ve completed the installation and configuration, run AXIS Installation Verifier from the main menu icon
More informationHybrid resampling methods for confidence intervals: comment
Title Hybrid resampling methods for confidence intervals: comment Author(s) Lee, SMS; Young, GA Citation Statistica Sinica, 2000, v. 10 n. 1, p. 43-46 Issued Date 2000 URL http://hdl.handle.net/10722/45352
More informationProcesses for the Intersection
7 Timing Processes for the Intersection In Chapter 6, you studied the operation of one intersection approach and determined the value of the vehicle extension time that would extend the green for as long
More informationImpressions of Canadians on social media platforms and their impact on the news
Impressions of Canadians on social media platforms and their impact on the news Signal Survey Summary submitted by Nanos to SIGNAL Leadership Communication Inc., February 2017 (Submission 2017-984) > Overall,
More informationConsumer aerial survey. Implementing Ofcom s UHF Strategy
Implementing Ofcom s UHF Strategy Research Publication date: 28 May 2014 Contents Section Page 1 Introduction 1 2 Key findings 3 3 Background 4 4 Survey methodology 9 5 Number of DTT households 12 6 Aerial
More informationNANOS. Trudeau sets yet another new high on the preferred PM tracking by Nanos
Trudeau sets yet another new high on the preferred PM tracking by Nanos Nanos Weekly Tracking ending August 5 th, 2016 (released August 9 th, - 6 am Eastern) NANOS At a glance Preferred Prime Minister
More informationTime Domain Simulations
Accuracy of the Computational Experiments Called Mike Steinberger Lead Architect Serial Channel Products SiSoft Time Domain Simulations Evaluation vs. Experimentation We re used to thinking of results
More informationDepartment of Computer Science, Cornell University. fkatej, hopkik, Contact Info: Abstract:
A Gossip Protocol for Subgroup Multicast Kate Jenkins, Ken Hopkinson, Ken Birman Department of Computer Science, Cornell University fkatej, hopkik, keng@cs.cornell.edu Contact Info: Phone: (607) 255-9199
More informationTrudeau remains strong on preferred PM measure tracked by Nanos
Trudeau remains strong on preferred PM measure tracked by Nanos Nanos Weekly Tracking ending May 27 th, 2016 (released May 31 st, - 6 am Eastern) NANOS At a glance Preferred Prime Minister Trudeau remains
More informationTrudeau top choice as PM, unsure second and at a 12 month high
Trudeau top choice as PM, unsure second and at a 12 month high Nanos Weekly Tracking ending October 14 th, 2016 (released October 18 th, - 6 am Eastern) NANOS At a glance Preferred Prime Minister Asked
More informationAlmost seven in ten Canadians continue to think Trudeau has the qualities of a good political leader in Nanos tracking
Almost seven in ten Canadians continue to think Trudeau has the qualities of a good political leader in Nanos tracking Nanos Weekly Tracking ending September 16 th, 2016 (released September 20 th, - 6
More informationTrudeau scores strongest on having the qualities of a good political leader
Trudeau scores strongest on having the qualities of a good political leader Nanos Weekly Tracking ending September 9 th, 2016 (released September 13 th, - 6 am Eastern) NANOS At a glance Preferred Prime
More informationThe Choice of Sampling Frequency and Product Acceptance Criteria to Assure Content Uniformity for Continuous Manufacturing Processes
The Choice of Sampling Frequency and Product Acceptance Criteria to Assure Content Uniformity for Continuous Manufacturing Processes Authors Tim Kramer Sal Garcia Jeff Hofer Xiaoyu Zhang Ian Leavesley
More informationSkip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video
Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video Mohamed Hassan, Taha Landolsi, Husameldin Mukhtar, and Tamer Shanableh College of Engineering American
More informationPositive trajectory for Trudeau continues hits a twelve month high on preferred PM and qualities of good political leader in Nanos tracking
Positive trajectory for Trudeau continues hits a twelve month high on preferred PM and qualities of good political leader in Nanos tracking Nanos Weekly Tracking ending August 12 th, 2016 (released August
More informationNANOS. Trudeau first choice as PM, unsure scores second and at a three year high
Trudeau first choice as PM, unsure scores second and at a three year high Nanos Weekly Tracking ending November 4 th, 2016 (released November 8 th, 2016-6 am Eastern) NANOS At a glance Preferred Prime
More informationA. Introduction 1. Title: Automatic Underfrequency Load Shedding Requirements
DRAFT 6 V4 Standard PRC-006- RFC-01 01/11/11 A. Introduction 1. Title: Automatic Underfrequency Load Shedding Requirements Deleted: Deleted: 10 Deleted: 20 9 2. Number: PRC 006 RFC 01. Purpose: To establish
More informationTrudeau hits 12 month high, Mulcair 12 month low in wake of Commons incident
Trudeau hits 12 month high, Mulcair 12 month low in wake of Commons incident Nanos Weekly Tracking ending May 20 th, 2016 (released May 24 th, - 6 am Eastern) NANOS At a glance Preferred Prime Minister
More informationGfK Audience Measurements & Insights FREQUENTLY ASKED QUESTIONS TV AUDIENCE MEASUREMENT IN THE KINGDOM OF SAUDI ARABIA
FREQUENTLY ASKED QUESTIONS TV AUDIENCE MEASUREMENT IN THE KINGDOM OF SAUDI ARABIA Why do we need a TV audience measurement system? TV broadcasters and their sales houses, advertisers and agencies interact
More informationPreferred Ottawa Public Library hours of operation GenPop Survey Summary Document 3
Preferred Public Library hours of operation GenPop Survey Summary Document 3 submitted by Nanos to Public Library, July 2017 (Submission 2017-1008) > Nanos residents say Saturdays are the most important
More information2.1 Telephone Follow-up Procedure
TELEPHONE SURVEY DEVELOPMENT ON THE CANADIAN LABOUR FORCE SURVEY 3. Douglas Drew and Richard G. 3aworski Statistics Canada Introduction A recently launched telephone survey development program at Statistics
More informationMusic Therapists Training Program by Hyogo Prefectural Administration
Music Therapists Training Program by Hyogo Prefectural Administration Presentation at the 15 th WFMT World Congress of Music Therapy July 4-8, 2017 in Tsukuba, Japan, by Takako TSUKUDA, Public Interest
More informationTesting Production Data Capture Quality
Testing Production Data Capture Quality K. Bradley Paxton, Steven P. Spiwak, Douglass Huang, and James K. McGarity ADI, LLC 200 Canal View Boulevard, Rochester, NY 14623 brad.paxton@adillc.net, steve.spiwak@adillc.net,
More informationAN EXPERIMENT WITH CATI IN ISRAEL
Paper presented at InterCasic 96 Conference, San Antonio, TX, 1996 1. Background AN EXPERIMENT WITH CATI IN ISRAEL Gad Nathan and Nilufar Aframian Hebrew University of Jerusalem and Israel Central Bureau
More informationAMERICAN NATIONAL STANDARD
Interface Practices Subcommittee AMERICAN NATIONAL STANDARD ANSI/SCTE 108 2018 Test Method for Dielectric Withstand of Coaxial Cable NOTICE The Society of Cable Telecommunications Engineers (SCTE) / International
More informationTHE UNIVERSITY OF QUEENSLAND
THE UNIVERSITY OF QUEENSLAND 1999 LIBRARY CUSTOMER SURVEY THE UNIVERSITY OF QUEENSLAND LIBRARY Survey October 1999 CONTENTS 1. INTRODUCTION... 1 1.1 BACKGROUND... 1 1.2 OBJECTIVES... 2 1.3 THE SURVEY PROCESS...
More informationDetection and demodulation of non-cooperative burst signal Feng Yue 1, Wu Guangzhi 1, Tao Min 1
International Conference on Applied Science and Engineering Innovation (ASEI 2015) Detection and demodulation of non-cooperative burst signal Feng Yue 1, Wu Guangzhi 1, Tao Min 1 1 China Satellite Maritime
More informationBuilding a Better Bach with Markov Chains
Building a Better Bach with Markov Chains CS701 Implementation Project, Timothy Crocker December 18, 2015 1 Abstract For my implementation project, I explored the field of algorithmic music composition
More informationMODELLING IMPLICATIONS OF SPLITTING EUC BAND 1
MODELLING IMPLICATIONS OF SPLITTING EUC BAND 1 1. BACKGROUND In respect of the consumption range 0-73.2 MWh pa, the finalised NDM proposals for 2007/08 (and for all previous years) apply a single EUC in
More informationHoneymoon is on - Trudeau up in preferred PM tracking by Nanos
Honeymoon is on - Trudeau up in preferred PM tracking by Nanos Nanos Weekly Tracking ending October 23 rd, 2015 (released October 27 th - 6 am Eastern) NANOS At a glance Preferred Prime Minister In the
More informationSpecial Article. Prior Publication Productivity, Grant Percentile Ranking, and Topic-Normalized Citation Impact of NHLBI Cardiovascular R01 Grants
Special Article Prior Publication Productivity, Grant Percentile Ranking, and Topic-Normalized Citation Impact of NHLBI Cardiovascular R01 Grants Jonathan R. Kaltman, Frank J. Evans, Narasimhan S. Danthi,
More informationEstimating. Proportions with Confidence. Chapter 10. Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc.
Estimating Chapter 10 Proportions with Confidence Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc. Principal Idea: Survey 150 randomly selected students and 41% think marijuana should be
More informationPitch correction on the human voice
University of Arkansas, Fayetteville ScholarWorks@UARK Computer Science and Computer Engineering Undergraduate Honors Theses Computer Science and Computer Engineering 5-2008 Pitch correction on the human
More informationData Representation. signals can vary continuously across an infinite range of values e.g., frequencies on an old-fashioned radio with a dial
Data Representation 1 Analog vs. Digital there are two ways data can be stored electronically 1. analog signals represent data in a way that is analogous to real life signals can vary continuously across
More informationThe Impact of the DTV Transition on Consumers and Consumer Choice. Overview of the DTV Transition Situation
The Impact of the DTV Transition on Consumers and Consumer Choice Session: Opportunity in Chaos Economics of the Digital TV Transition The Columbia Institute for Tele-Information Columbia University Barry
More informationKnoxville External Video Survey: Background & Status Report
Knoxville External Video Survey: Background & Status Report Tennessee Model Users Group Meeting October 24, 2007 Why conduct the survey? Background: Why conduct the survey? Why a video camera license plate
More informationRelationships Between Quantitative Variables
Chapter 5 Relationships Between Quantitative Variables Three Tools we will use Scatterplot, a two-dimensional graph of data values Correlation, a statistic that measures the strength and direction of a
More informationIMPROVING SIGNAL DETECTION IN SOFTWARE-BASED FACIAL EXPRESSION ANALYSIS
WORKING PAPER SERIES IMPROVING SIGNAL DETECTION IN SOFTWARE-BASED FACIAL EXPRESSION ANALYSIS Matthias Unfried, Markus Iwanczok WORKING PAPER /// NO. 1 / 216 Copyright 216 by Matthias Unfried, Markus Iwanczok
More informationhprints , version 1-1 Oct 2008
Author manuscript, published in "Scientometrics 74, 3 (2008) 439-451" 1 On the ratio of citable versus non-citable items in economics journals Tove Faber Frandsen 1 tff@db.dk Royal School of Library and
More informationInternational Journal of Library and Information Studies. An User Satisfaction about Library Resources and Services: A Study
An User Satisfaction about Library Resources and Services: A Study Dr. S. Ravi Professor Library and Information Science Wing Directorate of Distance Education Annamalai University Annamalainagar - 608002
More informationOpen access press vs traditional university presses on Amazon
Open access press vs traditional university presses on Amazon Rory McGreal (PhD),* Edward Acqua** * Professor & Assoc. VP, Research at Athabasca University. ** Analyst, Institutional Studies section of
More informationSimulation Supplement B
Simulation Supplement B Simulation Simulation: The act of reproducing the behavior of a system using a model that describes the processes of the system. Time Compression: The feature of simulations that
More informationResampling Statistics. Conventional Statistics. Resampling Statistics
Resampling Statistics Introduction to Resampling Probability Modeling Resample add-in Bootstrapping values, vectors, matrices R boot package Conclusions Conventional Statistics Assumptions of conventional
More informationViews on local news in the federal electoral district of Montmagny-L Islet-Kamouraska-Rivière-du-Loup
Views on local news in the federal electoral district of Montmagny-L Islet-Kamouraska-Rivière-du-Loup Montmagny-L Islet-Kamouraska-Rivière-du-Loup (FED) Survey Summary (Local Broadcasting) submitted by
More informationRelationships. Between Quantitative Variables. Chapter 5. Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc.
Relationships Chapter 5 Between Quantitative Variables Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc. Three Tools we will use Scatterplot, a two-dimensional graph of data values Correlation,
More informationPittsburg State University THESIS MANUAL. Approved by the Graduate Council April 13, 2005
Pittsburg State University THESIS MANUAL Approved by the Graduate Council April 13, 2005 1 INTRODUCTION The information contained in the Thesis Manual pertains to the technical aspects of thesis writing
More information