Chapter 21. Margin of Error. Intervals. Asymmetric Boxes Interpretation Examples. Chapter 21. Margin of Error

Size: px
Start display at page:

Download "Chapter 21. Margin of Error. Intervals. Asymmetric Boxes Interpretation Examples. Chapter 21. Margin of Error"

Transcription

1 Context Part VI Sampling Accuracy of Percentages Previously, we assumed that we knew the contents of the box and argued about chances for the draws based on this knowledge. In survey work, we frequently need to turn this reasoning, and argue from the draws to the box. This is called inference. Three main new ideas: method to estimate the SE error intervals simple random sample of 2500 voters. In the sample, 1328 people favor the candidate. This is simple random sample of 2500 voters. In the sample, 1328 people favor the candidate % = 53% 2500 Population Parameter Should he enter the primary? The crucial question is: how wrong is this estimate likely to be? Sample Statistic

2 simple random sample of 2500 voters. In the sample, 1328 people favor the candidate. The likely size of the chance error is given by the standard error, and to calculate that we need a box model: 0?? 1?? Population: 100,000 voters in the district Parameter: percentage of voters who favor the candidate Sample: 2500 people who were polled SD of the box = (1 0) (fraction of 1's) (fraction of 0's) Problem: We do not know the composition of the box. Statistic: percentage of voters in the sample who favor the candidate: 53% Solution: Substitute the fractions observed in the sample for the unknown fractions in the box. So SD of the box (1 0) 1, 328 1, 172 2, 500 2, SE for the sum = = 25 SE for the sample percentage = % = 1% 2, 500 This technique is called bootstrap. When sampling from a 0-1 box whose composition is unknown, the SD of the box can be estimated by substituting the fractions of 0's and 1's in the sample for the unknown fractions in the box. This estimate is good when the sample is reasonably large. Thus, the estimate of 53% is likely to be o by 1% or so. The candidate is very likely to win.

3 The margin of error (not in The margin of error (not in textbook) In the media, a margin of error is commonly reported for polls. textbook) This is just twice the standard error. intervals intervals In, 53% of the voters in the sample were in favor of the candidate. The SE for the percentage was estimated as 1%. How far can the population percentage (parameter) be from 53%? We know that a chance error of more than 2 SEs is unlikely. We can make condence intervals with any condence level. Some common levels are: estimate ± 1 SE: 68% condence interval estimate ± 2 SEs: 95% condence interval So let's go 2 SEs in each direction: (51%, 55%). estimate ± 3 SEs: 99.7% condence interval The is called a 95% condence interval for the population percentage. : we are about 95% condent that this interval captures the percentage of voters in the population who favor the candidate. These numbers are based on the normal approximation; the method only works if the normal approximation works The more asymmetric the box, the larger the sample size we need (because of the Central Limit Theorem, see Ch 18.5)

4 intervals of condence intervals Consider 10, 100, 1000, or 10,000 draws from the following boxes: 0 500, , , , , What does it mean that we are about 95% condent that the interval captures the population parameter? Remember that the population percentage is a xed number. Each time we take a dierent sample, we get a dierent sample percentage, and thus also a dierent estimate for the SE. If we would repeat this a million times, then 95% of the condence intervals contain the true population percentage, and 5% don't. Problem: after computing a condence interval, we don't know if it is one that contains the true parameter, or if it is one of the few that do not contain the parameter. Considerations Example 2 1 The methods in this chapter only work for simple random samples For more complicated sampling methods like cluster sampling, we need more complicated formulas For non-probability sampling methods, we basically have no formulas A survey organization takes a simple random sample of 1500 persons from residents in a large city. Among the sampled persons, 1035 were renters. 2 The sample size should be small relative to the population (say < 1/10th), so that we can ignore that we draw without replacement 3 For the bootstrap method to work, the sample size should be reasonably large Fill in the blanks: We estimate that the percentage of renters in the city is... This estimate is likely to be o by... or so. 4 For the normal approximation to work, the sample size should be reasonably large. The more asymmetric the box is, the larger the sample size we need. If possible, also construct a 95% condence interval for the percentage of renters.

5 Example 3 Example 3 A simple random sample of 6, year-olds in school was taken. Only 36.1% of the students in the sample knew that Chaucer wrote The Canterbury Tales, but 95.2% knew that Edison invented the light bulb. A simple random sample of 6, year-olds in school was taken. Only 36.1% of the students in the sample knew that Chaucer wrote The Canterbury Tales, but 95.2% knew that Edison invented the light bulb. (a) If possibly, nd a 95% con- dence interval for the percentage of all 17-year-olds in school who knew Chaucer wrote The Canterbury Tales. (b) If possible, nd a 95% con- dence interval for the percentage of all 17-year-olds in school who knew that Edison invented the light bulb.

Estimating. Proportions with Confidence. Chapter 10. Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc.

Estimating. 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 information

Subject: Florida U.S. Congressional District 13 Primary Election survey

Subject: Florida U.S. Congressional District 13 Primary Election survey 8601 4 th St. N., Suite 304 St. Petersburg, FL 33702 Phone: (727) 245-1962 Fax: (727) 577-7470 Email: info@stpetepolls.org Website: www.stpetepolls.org Matt Florell, President Subject: Florida U.S. Congressional

More information

Margin of Error. p(1 p) n 0.2(0.8) 900. Since about 95% of the data will fall within almost two standard deviations, we will use the formula

Margin of Error. p(1 p) n 0.2(0.8) 900. Since about 95% of the data will fall within almost two standard deviations, we will use the formula Name Margin of Error A survey of a sample population gathers information from a few people and then the results are used to reflect the opinions of a larger population. The reason that researchers and

More information

What is Statistics? 13.1 What is Statistics? Statistics

What is Statistics? 13.1 What is Statistics? Statistics 13.1 What is Statistics? What is Statistics? The collection of all outcomes, responses, measurements, or counts that are of interest. A portion or subset of the population. Statistics Is the science of

More information

Quantitative methods

Quantitative 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 information

Why t? TEACHER NOTES MATH NSPIRED. Math Objectives. Vocabulary. About the Lesson

Why t? TEACHER NOTES MATH NSPIRED. Math Objectives. Vocabulary. About the Lesson Math Objectives Students will recognize that when the population standard deviation is unknown, it must be estimated from the sample in order to calculate a standardized test statistic. Students will recognize

More information

Objective: 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. 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 information

SDS PODCAST EPISODE 96 FIVE MINUTE FRIDAY: THE BAYES THEOREM

SDS PODCAST EPISODE 96 FIVE MINUTE FRIDAY: THE BAYES THEOREM SDS PODCAST EPISODE 96 FIVE MINUTE FRIDAY: THE BAYES THEOREM This is Five Minute Friday episode number 96: The Bayes Theorem Welcome everybody back to the SuperDataScience podcast. Super excited to have

More information

Bootstrap Methods in Regression Questions Have you had a chance to try any of this? Any of the review questions?

Bootstrap Methods in Regression Questions Have you had a chance to try any of this? Any of the review questions? ICPSR Blalock Lectures, 2003 Bootstrap Resampling Robert Stine Lecture 3 Bootstrap Methods in Regression Questions Have you had a chance to try any of this? Any of the review questions? Getting class notes

More information

Subject: Florida Statewide Republican Primary Election survey conducted for FloridaPolitics.com

Subject: Florida Statewide Republican Primary Election survey conducted for FloridaPolitics.com 9887 4 th St. N., Suite 200 St. Petersburg, FL 33702 Phone: (727) 245-1962 Fax: (727) 577-7470 Email: info@stpetepolls.org Website: www.stpetepolls.org Matt Florell, President Subject: Florida Statewide

More information

UNIVERSITY OF CAMBRIDGE INTERNATIONAL EXAMINATIONS General Certificate of Education Ordinary Level

UNIVERSITY OF CAMBRIDGE INTERNATIONAL EXAMINATIONS General Certificate of Education Ordinary Level UNIVERSITY OF CAMBRIDGE INTERNATIONAL EXAMINATIONS General Certificate of Education Ordinary Level *0192736882* STATISTICS 4040/12 Paper 1 October/November 2013 Candidates answer on the question paper.

More information

Lecture 10: Release the Kraken!

Lecture 10: Release the Kraken! Lecture 10: Release the Kraken! Last time We considered some simple classical probability computations, deriving the socalled binomial distribution -- We used it immediately to derive the mathematical

More information

STAT 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) 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 information

Eisenberger with mayoral lead in Hamilton Largest number undecided

Eisenberger with mayoral lead in Hamilton Largest number undecided FOR IMMEDIATE RELEASE Eisenberger with mayoral lead in Largest number undecided SEPTEMBER 26 th, 2014 In a random sampling of public opinion taken by the Forum Poll among 839 voters, just more than one

More information

Conditional Probability and Bayes

Conditional Probability and Bayes Conditional Probability and Bayes Chapter 2 Lecture 7 Yiren Ding Shanghai Qibao Dwight High School March 15, 2016 Yiren Ding Conditional Probability and Bayes 1 / 20 Outline 1 Bayes Theorem 2 Application

More information

How Large a Sample? CHAPTER 24. Issues in determining sample size

How 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 information

Resampling Statistics. Conventional Statistics. Resampling Statistics

Resampling 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 information

The Fox News Eect:Media Bias and Voting S. DellaVigna and E. Kaplan (2007)

The Fox News Eect:Media Bias and Voting S. DellaVigna and E. Kaplan (2007) The Fox News Eect:Media Bias and Voting S. DellaVigna and E. Kaplan (2007) Anna Airoldi Igor Cerasa IGIER Visiting Students Presentation March 21st, 2014 Research Questions Does the media have an impact

More information

Northern Dakota County Cable Communications Commission ~

Northern Dakota County Cable Communications Commission ~ Northern Dakota County Cable Communications Commission ~ Cable Subscriber Survey April 2014 This document presents data, analysis and interpretation of study findings by Group W Communications, L.L.C.

More information

MATH 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 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 information

Chapter 1 Midterm Review

Chapter 1 Midterm Review Name: Class: Date: Chapter 1 Midterm Review Multiple Choice Identify the choice that best completes the statement or answers the question. 1. A survey typically records many variables of interest to the

More information

Chapter 7 Probability

Chapter 7 Probability Chapter 7 Probability Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc. 7.1 Random Circumstances Random circumstance is one in which the outcome is unpredictable. Case Study 1.1 Alicia Has

More information

COMP Test on Psychology 320 Check on Mastery of Prerequisites

COMP 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 information

China s Overwhelming Contribution to Scientific Publications

China s Overwhelming Contribution to Scientific Publications China s Overwhelming Contribution to Scientific Publications Qingnan Xie, Nanjing University of Science &Technology Labor and Worklife Program, Harvard Law School. Richard B. Freeman, Harvard & NBER From

More information

Chapter 27. Inferences for Regression. Remembering Regression. An Example: Body Fat and Waist Size. Remembering Regression (cont.)

Chapter 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 information

Subject: Florida Statewide Republican Governor Primary Election survey conducted for FloridaPolitics.com

Subject: Florida Statewide Republican Governor Primary Election survey conducted for FloridaPolitics.com 9887 4 th St. N., Suite 200 St. Petersburg, FL 33702 Phone: (727) 245-1962 Fax: (727) 577-7470 Email: info@stpetepolls.org Website: www.stpetepolls.org Matt Florell, President Subject: Florida Statewide

More information

AP Statistics Sec 5.1: An Exercise in Sampling: The Corn Field

AP 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 information

BARB Establishment Survey Annual Data Report: Volume 1 Total Network and Appendices

BARB 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 information

A Majority of Americans Use Apps to Watch Streaming Content on Their Televisions

A Majority of Americans Use Apps to Watch Streaming Content on Their Televisions A Majority of Americans Use Apps to Watch Streaming Content on Their Televisions Men, Younger Adults, Higher Income Earners, and Those with a College Degree Are Among Those Most Likely to Use a Variety

More information

Monday 15 May 2017 Afternoon Time allowed: 1 hour 30 minutes

Monday 15 May 2017 Afternoon Time allowed: 1 hour 30 minutes Oxford Cambridge and RSA AS Level Psychology H167/01 Research methods Monday 15 May 2017 Afternoon Time allowed: 1 hour 30 minutes *6727272307* You must have: a calculator a ruler * H 1 6 7 0 1 * First

More information

Community Orchestras in Australia July 2012

Community Orchestras in Australia July 2012 Summary The Music in Communities Network s research agenda includes filling some statistical gaps in our understanding of the community music sector. We know that there are an enormous number of community-based

More information

BARB Establishment Survey Quarterly Data Report: Total Network

BARB 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 information

The Relationship Between Movie theater Attendance and Streaming Behavior. Survey Findings. December 2018

The 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 information

Key Maths Facts to Memorise Question and Answer

Key Maths Facts to Memorise Question and Answer Key Maths Facts to Memorise Question and Answer Ways of using this booklet: 1) Write the questions on cards with the answers on the back and test yourself. 2) Work with a friend to take turns reading a

More information

Use black ink or black ball-point pen. Pencil should only be used for drawing. *

Use black ink or black ball-point pen. Pencil should only be used for drawing. * General Certificate of Education June 2009 Advanced Subsidiary Examination MATHEMATICS Unit Statistics 1B MS/SS1B STATISTICS Unit Statistics 1B Wednesday 20 May 2009 1.30 pm to 3.00 pm For this paper you

More information

AGAINST ALL ODDS EPISODE 22 SAMPLING DISTRIBUTIONS TRANSCRIPT

AGAINST ALL ODDS EPISODE 22 SAMPLING DISTRIBUTIONS TRANSCRIPT AGAINST ALL ODDS EPISODE 22 SAMPLING DISTRIBUTIONS TRANSCRIPT 1 FUNDER CREDITS Funding for this program is provided by Annenberg Learner. 2 INTRO Pardis Sabeti Hi, I m Pardis Sabeti and this is Against

More information

MATH& 146 Lesson 11. Section 1.6 Categorical Data

MATH& 146 Lesson 11. Section 1.6 Categorical Data MATH& 146 Lesson 11 Section 1.6 Categorical Data 1 Frequency The first step to organizing categorical data is to count the number of data values there are in each category of interest. We can organize

More information

Before the Federal Communications Commission Washington, D.C ) ) ) ) ) ) ) ) ) REPORT ON CABLE INDUSTRY PRICES

Before 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 information

International Affairs Department, Telecommunications Bureau

International Affairs Department, Telecommunications Bureau International Affairs Department, Bureau Biweekly Newsletter of the Ministry of Internal Affairs and Communications (MIC), Japan Vol. 17 No. 62 May July 12, 7, 2006 ISSN 1349-7987 Please feel free to use

More information

More About Regression

More About Regression Regression Line for the Sample Chapter 14 More About Regression is spoken as y-hat, and it is also referred to either as predicted y or estimated y. b 0 is the intercept of the straight line. The intercept

More information

NEW INSIGHTS ON TODAY S COMMUTERS

NEW INSIGHTS ON TODAY S COMMUTERS The State of In-Car Audio NEW INSIGHTS ON TODAY S COMMUTERS With Findings From Edison Research s Hacking the Commuter Code Study APRIL 2016 Americans Have A Complicated Relationship With Their Cars So,

More information

Bart vs. Lisa vs. Fractions

Bart vs. Lisa vs. Fractions Bart vs. Lisa vs. Fractions The Simpsons is a long-running animated series about a boy named Bart, his younger sister, Lisa, their family, and their town. One episode in the 14th season featured an unexpected

More information

STAYING INFORMED ACROSS THE GARDEN STATE WHERE DO YOU GO AND WHAT DO YOU KNOW?

STAYING INFORMED ACROSS THE GARDEN STATE WHERE DO YOU GO AND WHAT DO YOU KNOW? For immediate release Thursday, April 20, 2017 7 pages Contact: Dan Cassino 973.896.7072; dcassino@fdu.edu @dancassino STAYING INFORMED ACROSS THE GARDEN STATE WHERE DO YOU GO AND WHAT DO YOU KNOW? Fairleigh

More information

unbiased , is zero. Yï) + iab Fuller and Burmeister [4] suggested the estimator: N =Na +Nb + Nab Na +NB =Nb +NA.

unbiased , 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 information

Penultimate Check-Up on Election 42: LIBERALS OPENING UP DAYLIGHT?

Penultimate Check-Up on Election 42: LIBERALS OPENING UP DAYLIGHT? www.ekospolitics.ca Penultimate Check-Up on Election 42: LIBERALS OPENING UP DAYLIGHT? [Ottawa October, 1] With less than 24 hours to go until the polls open, it appears as though vote intentions are relatively

More information

Box Plots. So that I can: look at large amount of data in condensed form.

Box Plots. So that I can: look at large amount of data in condensed form. LESSON 5 Box Plots LEARNING OBJECTIVES Today I am: creating box plots. So that I can: look at large amount of data in condensed form. I ll know I have it when I can: make observations about the data based

More information

Distribution of Data and the Empirical Rule

Distribution of Data and the Empirical Rule 302360_File_B.qxd 7/7/03 7:18 AM Page 1 Distribution of Data and the Empirical Rule 1 Distribution of Data and the Empirical Rule Stem-and-Leaf Diagrams Frequency Distributions and Histograms Normal Distributions

More information

B291B. MATHEMATICS B (MEI) Paper 1 Section B (Foundation Tier) GENERAL CERTIFICATE OF SECONDARY EDUCATION. Friday 9 January 2009 Morning

B291B. MATHEMATICS B (MEI) Paper 1 Section B (Foundation Tier) GENERAL CERTIFICATE OF SECONDARY EDUCATION. Friday 9 January 2009 Morning F GENERAL CERTIFICATE OF SECONDARY EDUCATION MATHEMATICS B (MEI) Paper 1 Section B (Foundation Tier) B291B *CUP/T62437* Candidates answer on the question paper OCR Supplied Materials: None Other Materials

More information

1 Lesson 11: Antiderivatives of Elementary Functions

1 Lesson 11: Antiderivatives of Elementary Functions 1 Lesson 11: Antiderivatives of Elementary Functions Chapter 6 Material: pages 237-252 in the textbook: The material in this lesson covers The definition of the antiderivative of a function of one variable.

More information

An Effective Filtering Algorithm to Mitigate Transient Decaying DC Offset

An Effective Filtering Algorithm to Mitigate Transient Decaying DC Offset An Effective Filtering Algorithm to Mitigate Transient Decaying DC Offset By: Abouzar Rahmati Authors: Abouzar Rahmati IS-International Services LLC Reza Adhami University of Alabama in Huntsville April

More information

Confidence Intervals for Radio Ratings Estimators

Confidence 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 information

Centre for Economic Policy Research

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 information

Task-based Activity Cover Sheet

Task-based Activity Cover Sheet Task-based Activity Cover Sheet Task Title: Carpenter Using Construction Design Software Learner Name: Date Started: Date Completed: Successful Completion: Yes No Goal Path: Employment Apprenticeship Secondary

More information

STAT 250: Introduction to Biostatistics LAB 6

STAT 250: Introduction to Biostatistics LAB 6 STAT 250: Introduction to Biostatistics LAB 6 Dr. Kari Lock Morgan Sampling Distributions In this lab, we ll explore sampling distributions using StatKey: www.lock5stat.com/statkey. We ll be using StatKey,

More information

expressed on operational issues are those of the authors and not necessarily those of the U.S. Census Bureau.

expressed 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 information

Validity. What Is It? Types We Will Discuss. The degree to which an inference from a test score is appropriate or meaningful.

Validity. What Is It? Types We Will Discuss. The degree to which an inference from a test score is appropriate or meaningful. Validity 4/8/2003 PSY 721 Validity 1 What Is It? The degree to which an inference from a test score is appropriate or meaningful. A test may be valid for one application but invalid for an another. A test

More information

Analysis of Seabright study on demand for Sky s pay TV services. Annex 7 to pay TV phase three document

Analysis of Seabright study on demand for Sky s pay TV services. Annex 7 to pay TV phase three document Analysis of Seabright study on demand for Sky s pay TV services Annex 7 to pay TV phase three document Publication date: 26 June 2009 Comments on the study: The e ect of DTT availability on household s

More information

Background Information. Instructions. Problem Statement. HOMEWORK INSTRUCTIONS Homework #5 Nielsen Television Ratings Problem

Background Information. Instructions. Problem Statement. HOMEWORK INSTRUCTIONS Homework #5 Nielsen Television Ratings Problem Background Information HOMEWORK INSTRUCTIONS Over the course of a given week, the vast majority of Americans watch at least some amount of television. Since most television shows are paid for by the sales

More information

AP Statistics Sampling. Sampling Exercise (adapted from a document from the NCSSM Leadership Institute, July 2000).

AP 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 information

Comparative Study of Electoral Systems (CSES) Module 3: Sample Design and Data Collection Report June 05, 2006

Comparative 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 information

Consonance and Dissonance Activities *

Consonance and Dissonance Activities * OpenStax-CNX module: m11999 1 Consonance and Dissonance Activities * Catherine Schmidt-Jones This work is produced by OpenStax-CNX and licensed under the Creative Commons Attribution License 3.0 Abstract

More information

Views 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 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 information

BIBLIOGRAPHIC DATA: A DIFFERENT ANALYSIS PERSPECTIVE. Francesca De Battisti *, Silvia Salini

BIBLIOGRAPHIC DATA: A DIFFERENT ANALYSIS PERSPECTIVE. Francesca De Battisti *, Silvia Salini Electronic Journal of Applied Statistical Analysis EJASA (2012), Electron. J. App. Stat. Anal., Vol. 5, Issue 3, 353 359 e-issn 2070-5948, DOI 10.1285/i20705948v5n3p353 2012 Università del Salento http://siba-ese.unile.it/index.php/ejasa/index

More information

Sampling Plans. Sampling Plan - Variable Physical Unit Sample. Sampling Application. Sampling Approach. Universe and Frame Information

Sampling 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 information

GROWING VOICE COMPETITION SPOTLIGHTS URGENCY OF IP TRANSITION By Patrick Brogan, Vice President of Industry Analysis

GROWING VOICE COMPETITION SPOTLIGHTS URGENCY OF IP TRANSITION By Patrick Brogan, Vice President of Industry Analysis RESEARCH BRIEF NOVEMBER 22, 2013 GROWING VOICE COMPETITION SPOTLIGHTS URGENCY OF IP TRANSITION By Patrick Brogan, Vice President of Industry Analysis An updated USTelecom analysis of residential voice

More information

Cambridge International Examinations Cambridge International Advanced Subsidiary and Advanced Level

Cambridge International Examinations Cambridge International Advanced Subsidiary and Advanced Level Cambridge International Examinations Cambridge International Advanced Subsidiary and Advanced Level CANDIDATE NAME *4084773853* CENTRE NUMBER CANDIDATE NUMBER MATHEMATICS 9709/63 Paper 6 Probability& Statistics

More information

North Carolina Standard Course of Study - Mathematics

North Carolina Standard Course of Study - Mathematics A Correlation of To the North Carolina Standard Course of Study - Mathematics Grade 4 A Correlation of, Grade 4 Units Unit 1 - Arrays, Factors, and Multiplicative Comparison Unit 2 - Generating and Representing

More information

NAA 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 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 information

Department of MBA, School of Communication and Management Studies, Nalukettu, Kerala, India

Department of MBA, School of Communication and Management Studies, Nalukettu, Kerala, India Original Article International Multidisciplinary Research Journal 2015, 5: 16-22 http://scienceflora.org/journals/index.php/imrj/ doi: 10.19071/imrj.2015.v5.3174 Viewership analysis of news channels with

More information

AN EXPERIMENT WITH CATI IN ISRAEL

AN 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 information

Personalized TV Recommendation with Mixture Probabilistic Matrix Factorization

Personalized TV Recommendation with Mixture Probabilistic Matrix Factorization Personalized TV Recommendation with Mixture Probabilistic Matrix Factorization Huayu Li, Hengshu Zhu #, Yong Ge, Yanjie Fu +,Yuan Ge Computer Science Department, UNC Charlotte # Baidu Research-Big Data

More information

TeeJay Publishers. Curriculum for Excellence. Course Planner - Level 1

TeeJay Publishers. Curriculum for Excellence. Course Planner - Level 1 TeeJay Publishers Curriculum for Excellence Course Planner Level 1 To help schools develop their courses, TeeJay Publishers has produced a Course Planner for CfE Level 1. This Planner from TeeJay provides

More information

3. Population and Demography

3. Population and Demography 3. Population and Demography Population Births and Deaths Marriage and Divorce 110 Statistical Yearbook of Abu Dhabi 2015 Statistical Yearbook of Abu Dhabi 2015 111 3. Population and Demography The population

More information

OCTAVE C 3 D 3 E 3 F 3 G 3 A 3 B 3 C 4 D 4 E 4 F 4 G 4 A 4 B 4 C 5 D 5 E 5 F 5 G 5 A 5 B 5. Middle-C A-440

OCTAVE C 3 D 3 E 3 F 3 G 3 A 3 B 3 C 4 D 4 E 4 F 4 G 4 A 4 B 4 C 5 D 5 E 5 F 5 G 5 A 5 B 5. Middle-C A-440 DSP First Laboratory Exercise # Synthesis of Sinusoidal Signals This lab includes a project on music synthesis with sinusoids. One of several candidate songs can be selected when doing the synthesis program.

More information

Mixed Models Lecture Notes By Dr. Hanford page 151 More Statistics& SAS Tutorial at Type 3 Tests of Fixed Effects

Mixed Models Lecture Notes By Dr. Hanford page 151 More Statistics& SAS Tutorial at  Type 3 Tests of Fixed Effects Assessing fixed effects Mixed Models Lecture Notes By Dr. Hanford page 151 In our example so far, we have been concentrating on determining the covariance pattern. Now we ll look at the treatment effects

More information

Reconstruction of Ca 2+ dynamics from low frame rate Ca 2+ imaging data CS229 final project. Submitted by: Limor Bursztyn

Reconstruction of Ca 2+ dynamics from low frame rate Ca 2+ imaging data CS229 final project. Submitted by: Limor Bursztyn Reconstruction of Ca 2+ dynamics from low frame rate Ca 2+ imaging data CS229 final project. Submitted by: Limor Bursztyn Introduction Active neurons communicate by action potential firing (spikes), accompanied

More information

The Role of Dice in Election Audits Extended Abstract

The Role of Dice in Election Audits Extended Abstract The Role of Dice in Election Audits Extended Abstract Arel Cordero arel@cs.berkeley.edu David Wagner daw@cs.berkeley.edu June 16, 2006 David Dill dill@cs.stanford.edu Abstract Random audits are a powerful

More information

Professor Weissman s Algebra Classroom

Professor Weissman s Algebra Classroom Combine Like Terms Unit #12 2007 Prof Weissman s Software Tel: 1-347-528-7837 mathprof@hotmail.com Professor Weissman s Algebra Classroom Martin Weissman, Jonathan S. Weissman, Tamara Farber, & Keith Monse

More information

Common assumptions in color characterization of projectors

Common assumptions in color characterization of projectors Common assumptions in color characterization of projectors Arne Magnus Bakke 1, Jean-Baptiste Thomas 12, and Jérémie Gerhardt 3 1 Gjøvik university College, The Norwegian color research laboratory, Gjøvik,

More information

OPIOIDS IN THE GARDEN STATE

OPIOIDS IN THE GARDEN STATE OPIOIDS IN THE GARDEN STATE Ashley Koning, PhD Assistant Research Professor, Director Eagleton Center for Public Interest Polling Eagleton Institute of Politics Rutgers University-New Brunswick Itzhak

More information

Frictions and the elasticity of taxable income: evidence from bunching at tax thresholds in the UK

Frictions and the elasticity of taxable income: evidence from bunching at tax thresholds in the UK Frictions and the elasticity of taxable income: evidence from bunching at tax thresholds in the UK Barra Roantree, Stuart Adam, James Browne, David Phillips Workshop on the incidence and labour market

More information

Experimental Results from a Practical Implementation of a Measurement Based CAC Algorithm. Contract ML704589 Final report Andrew Moore and Simon Crosby May 1998 Abstract Interest in Connection Admission

More information

Internet Passes Radio, Closes in on Television as Most Essential Medium in American Life

Internet Passes Radio, Closes in on Television as Most Essential Medium in American Life Internet Passes Radio, Closes in on Television as Most Essential Medium in American Life Internet trails only television as most essential medium 6 Five years later Media Perceptions from 2002 to 2007

More information

BOOK READING IN NEW ZEALAND

BOOK READING IN NEW ZEALAND HORIZON RESEARCH LIMITED BOOK READING IN NEW ZEALAND August 2018 Conducted for the NEW ZEALAND BOOK COUNCIL Book reading in New Zealand 08/2018 New Zealand Book Council 1 CONTENTS EXECUTIVE SUMMARY...4

More information

Algebra I Module 2 Lessons 1 19

Algebra I Module 2 Lessons 1 19 Eureka Math 2015 2016 Algebra I Module 2 Lessons 1 19 Eureka Math, Published by the non-profit Great Minds. Copyright 2015 Great Minds. No part of this work may be reproduced, distributed, modified, sold,

More information

Measuring Variability for Skewed Distributions

Measuring Variability for Skewed Distributions Measuring Variability for Skewed Distributions Skewed Data and its Measure of Center Consider the following scenario. A television game show, Fact or Fiction, was canceled after nine shows. Many people

More information

MATH 214 (NOTES) Math 214 Al Nosedal. Department of Mathematics Indiana University of Pennsylvania. MATH 214 (NOTES) p. 1/3

MATH 214 (NOTES) Math 214 Al Nosedal. Department of Mathematics Indiana University of Pennsylvania. MATH 214 (NOTES) p. 1/3 MATH 214 (NOTES) Math 214 Al Nosedal Department of Mathematics Indiana University of Pennsylvania MATH 214 (NOTES) p. 1/3 CHAPTER 1 DATA AND STATISTICS MATH 214 (NOTES) p. 2/3 Definitions. Statistics is

More information

Record your answers and work on the separate answer sheet provided.

Record your answers and work on the separate answer sheet provided. MATH 106 FINAL EXAMINATION This is an open-book exam. You may refer to your text and other course materials as you work on the exam, and you may use a calculator. You must complete the exam individually.

More information

Statistics For Dummies PDF

Statistics For Dummies PDF Statistics For Dummies PDF Statistics For Dummies, 2nd Edition (9781119293521) was previously published as Statistics For Dummies, 2nd Edition (9780470911082). While this version features a new Dummies

More information

Friday 17 May 2013 Morning

Friday 17 May 2013 Morning Friday 17 May 2013 Morning A2 GCE MATHEMATICS 4737/01 Decision Mathematics 2 PRINTED ANSWER BOOK *4715610613* Candidates answer on this Printed Answer Book. OCR supplied materials: Question Paper 4737/01

More information

Lesson 7: Measuring Variability for Skewed Distributions (Interquartile Range)

Lesson 7: Measuring Variability for Skewed Distributions (Interquartile Range) : Measuring Variability for Skewed Distributions (Interquartile Range) Exploratory Challenge 1: Skewed Data and its Measure of Center Consider the following scenario. A television game show, Fact or Fiction,

More information

Why Engineers Ignore Cable Loss

Why Engineers Ignore Cable Loss Why Engineers Ignore Cable Loss By Brig Asay, Agilent Technologies Companies spend large amounts of money on test and measurement equipment. One of the largest purchases for high speed designers is a real

More information

Ferenc, Szani, László Pitlik, Anikó Balogh, Apertus Nonprofit Ltd.

Ferenc, Szani, László Pitlik, Anikó Balogh, Apertus Nonprofit Ltd. Pairwise object comparison based on Likert-scales and time series - or about the term of human-oriented science from the point of view of artificial intelligence and value surveys Ferenc, Szani, László

More information

Viewers and Voters: Attitudes to television coverage of the 2005 General Election

Viewers and Voters: Attitudes to television coverage of the 2005 General Election Viewers and Voters: Attitudes to television coverage of the 2005 General Election Research Study conducted by ICM Research on behalf of Ofcom Please note that figures for Five and Sky News in Table 2 (Perceptions

More information

Comparing gifts to purchased materials: a usage study

Comparing gifts to purchased materials: a usage study Library Collections, Acquisitions, & Technical Services 24 (2000) 351 359 Comparing gifts to purchased materials: a usage study Rob Kairis* Kent State University, Stark Campus, 6000 Frank Ave. NW, Canton,

More information

Machine Vision System for Color Sorting Wood Edge-Glued Panel Parts

Machine Vision System for Color Sorting Wood Edge-Glued Panel Parts Machine Vision System for Color Sorting Wood Edge-Glued Panel Parts Q. Lu, S. Srikanteswara, W. King, T. Drayer, R. Conners, E. Kline* The Bradley Department of Electrical and Computer Eng. *Department

More information

Western Statistics Teachers Conference 2000

Western Statistics Teachers Conference 2000 Teaching Using Ratios 13 Mar, 2000 Teaching Using Ratios 1 Western Statistics Teachers Conference 2000 March 13, 2000 MILO SCHIELD Augsburg College www.augsburg.edu/ppages/schield schield@augsburg.edu

More information

Suppose you make $1000 a week. Your company is in dire straits, and so you have to take a 50% pay cut.

Suppose you make $1000 a week. Your company is in dire straits, and so you have to take a 50% pay cut. Station #5 Statisticulation Read the following joke: A man goes to a roadside diner where the special is "Rabbit Stew." He asks the waiter whether it really is rabbit in the stew. "Well, actually it's

More information

Section 5.2: Organizing and Graphing Categorical

Section 5.2: Organizing and Graphing Categorical Section 5.2: Organizing and Graphing Categorical Data Objective: Create a frequency table. Data is being collected all the time by businesses, governments, and researchers. The data can range from small

More information

A Study of Predict Sales Based on Random Forest Classification

A Study of Predict Sales Based on Random Forest Classification , pp.25-34 http://dx.doi.org/10.14257/ijunesst.2017.10.7.03 A Study of Predict Sales Based on Random Forest Classification Hyeon-Kyung Lee 1, Hong-Jae Lee 2, Jaewon Park 3, Jaehyun Choi 4 and Jong-Bae

More information