CONCLUSION The annual increase for optical scanner cost may be due partly to inflation and partly to special demands by the State.

Similar documents
HOSU Licensed Programs Page 1 of 7

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

Voting System Qualification Test Report Dominion Voting Systems, Inc. GEMS Release , Version 1

2018 All-State Chorus

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

Algebra I Module 2 Lessons 1 19

Chapter 1 Midterm Review

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

Problem Points Score USE YOUR TIME WISELY USE CLOSEST DF AVAILABLE IN TABLE SHOW YOUR WORK TO RECEIVE PARTIAL CREDIT

THE FAIR MARKET VALUE

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

Music Teacher Packet INFORMATION AND GUIDELINES

Secretary of State Bruce McPherson State of California PARALLEL MONITORING PROGRAM NOVEMBER 7, 2006 GENERAL ELECTION

Measuring Variability for Skewed Distributions

DV: Liking Cartoon Comedy

Libraries as Repositories of Popular Culture: Is Popular Culture Still Forgotten?

More About Regression

Audit of Time Warner Communications Cable Franchise Fees

2019 All-State Chorus Information

K-Pop Idol Industry Minhyung Lee

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

FMEA All-State Orff Ensemble Music Teacher Packet INFORMATION AND GUIDELINES

FMEA All-State Orff Ensemble Music Teacher Packet INFORMATION AND GUIDELINES

FIM INTERNATIONAL SURVEY ON ORCHESTRAS

Blueline, Linefree, Accuracy Ratio, & Moving Absolute Mean Ratio Charts

WILLIAMSON LAW BOOK COMPANY

TI-Inspire manual 1. Real old version. This version works well but is not as convenient entering letter

SECTION 7: Troubleshoot

Voting System Qualification Test Report Election Systems & Software, LLC

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

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

FMEA All-State Orff Ensemble Music Teacher Packet INFORMATION AND GUIDELINES

Voting System Qualification Test Report Dominion Voting Systems, Inc. Sequoia WinEDS Release , Version 1

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

Voting System Qualification Test Report Election Systems & Software, LLC

STAT 113: Statistics and Society Ellen Gundlach, Purdue University. (Chapters refer to Moore and Notz, Statistics: Concepts and Controversies, 8e)

New York State Board of Elections Voting Machine Replacement Project Task List Revised

Trudeau remains strong on preferred PM measure tracked by Nanos

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

The Executive Summary of Senate Bill 2106

Trudeau hits 12 month high, Mulcair 12 month low in wake of Commons incident

A year later, Trudeau remains near post election high on perceptions of having the qualities of a good political leader

International Comparison on Operational Efficiency of Terrestrial TV Operators: Based on Bootstrapped DEA and Tobit Regression

With Sticky Notes, you re front-page news!

Honeymoon is on - Trudeau up in preferred PM tracking by Nanos

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

WEALTHCLASSES PUBLISHING

Technical Appendices to: Is Having More Channels Really Better? A Model of Competition Among Commercial Television Broadcasters

CHILD SUPPORT GUIDELINES CHART

Chapter 1. Voting Equipment Testing

Quantitative methods

Moving on from MSTAT. March The University of Reading Statistical Services Centre Biometrics Advisory and Support Service to DFID

Northern Dakota County Cable Communications Commission ~

Warren County Port Authority

What is Statistics? 13.1 What is Statistics? Statistics

Southwest Florida Water Management District

NANOS. Trudeau sets yet another new high on the preferred PM tracking by Nanos

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

Almost seven in ten Canadians continue to think Trudeau has the qualities of a good political leader in Nanos tracking

Trudeau top choice as PM, unsure second and at a 12 month high

Most Canadians think the Prime Minister s trip to India was not a success

Trudeau scores strongest on having the qualities of a good political leader

Jefferson Parish Film Industry Incentives Program. 1. Purpose and Description of Jefferson Parish Film Industry Incentive Rebate Program

NANOS. Trudeau first choice as PM, unsure scores second and at a three year high

Positive trajectory for Trudeau continues hits a twelve month high on preferred PM and qualities of good political leader in Nanos tracking

AN EXPERIMENT WITH CATI IN ISRAEL

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

Best Pat-Tricks on Model Diagnostics What are they? Why use them? What good do they do?

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

2005 IOWA LAND VALUE SURVEY: OVERVIEW

Signal Survey Summary. submitted by Nanos to Signal Leadership Communication Inc., July 2018 (Submission )

NYE COUNTY AGENDA INFORMATION FORM

Sample Analysis Design. Element2 - Basic Software Concepts (cont d)

ELECTION JUDGE/COORDINATOR HANDBOOK GENERAL ELECTION 2018 CHAPTER 6

I. Model. Q29a. I love the options at my fingertips today, watching videos on my phone, texting, and streaming films. Main Effect X1: Gender

Committee Members: Attendees:

Document Analysis Support for the Manual Auditing of Elections

AUDIOVISUAL TREATY COPRODUCTIONS GOVERNED BY CANADIAN TREATIES THAT HAVE ENTERED INTO FORCE AS OF JULY 1, 2014

2016 Cord Cutter & Cord Never Study

Setting Goals for Your Library. And getting the funding to reach them

Boyle County Public Library 2018 Kentucky Annual Report of Public Libraries

Paired plot designs experience and recommendations for in field product evaluation at Syngenta

Analysis of Film Revenues: Saturated and Limited Films Megan Gold

As Reported by the House Finance Committee. 132nd General Assembly Regular Session Sub. S. B. No

California Community Colleges Library/Learning Resources Data Survey

Characterization and improvement of unpatterned wafer defect review on SEMs

COMP Test on Psychology 320 Check on Mastery of Prerequisites

Relationships Between Quantitative Variables

High-Definition Screens for Architecture Studios: Digital Media Pedagogy Integration

Views on local news in the federal electoral district of Montmagny-L Islet-Kamouraska-Rivière-du-Loup

2012 Inspector Survey Analysis Report. November 6, 2012 Presidential General Election

GLM Example: One-Way Analysis of Covariance

Technical Theater Certificate

Venice Chorale Inc. To serve a regional audience by promoting the art of choral singing through vocal excellence and multigenerational

Approve the meeting minutes from November 8, 2016, 8:00 a.m.; and October 13, 2016, 6:00 p.m.

Troubleshooting Guide for E-Poll Book

Confidence Intervals for Radio Ratings Estimators

Sampling: What you don t know can hurt you. Juan Muñoz

GfK Audience Measurements & Insights FREQUENTLY ASKED QUESTIONS TV AUDIENCE MEASUREMENT IN THE KINGDOM OF SAUDI ARABIA

Relationships. Between Quantitative Variables. Chapter 5. Copyright 2006 Brooks/Cole, a division of Thomson Learning, Inc.

Transcription:

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. By Rosemarie Myerson and Richard Myerson (contact romyerson@comcast.net) 12/1/05 PURPOSE This project was undertaken to study the changes in total expenditures by Florida s 67 Supervisor of Elections offices before and after electronic touchscreen voting was instituted and to compare the effect of the type voting system on costs. BACKGROUND Florida mandated that all counties replace punch cards and other non-electronic voting systems with either optical scanners or touch screen voting machines prior to the 2002 elections. The purchase costs for the new voting equipment were reimbursed to the Supervisor of Elections office by the county s commissioners so that the machine purchasing expenditures were never included in the Supervisor of Election s annual expenditures. Counties that already owned optical scanners before 2001 did not have to change systems. There were 13 counties that responded completely to this survey that did not need to change their voting machines since they were already using optical scanners. METHOD We requested data from the 67 counties in Florida (see enclosed copy of request letter). Despite the fact that 50 counties responded, we were limited to analyzing the data of 33 counties because the other counties could not provide full data on the number of registered voters and /or total expenditures for the years selected. To compare changes in the costs for each county for touchscreens versus optical scanners, total annual expenditures from the immediate pre- touchscreen period (2000 and 2001) were compared with the post- touch screen data (2003 and 2004). These four years were used in order to include in each period one presidential election year and one with no federal elections. Data from 2002 was excluded because in 2002 all but 13 of the 33 counties changed their voting systems which probably engendered special expenditures for education, training, special handling and storage. Also many counties did not include 1999 data so we could not compare three years pre- to three years posttouch screen purchase. ANALYSIS A comparison of the difference in expenditures per 1000 voters of the 11 counties with touchscreen systems versus those 22 counties with optical scanning systems for the 2003/2004 period could not be meaningful for the following reasons: 1) County size had an effect on the cost, Chart 1 shows a scatter plot of the 2003/2004 data for each county s costs per thousand voters versus the number of registered voters. The counties with less than 40,000 registered voters had higher costs per 1000 voters than the larger counties. This unusually high average annual expenditure implies some minimum costs for all counties independent of size of voting population. 2) There are also many unknown expenditure variables in county to county data such as what functions are included in each county s annual expenditures, some counties use different accounting 1

protocols, some show debt service as an expense. These and uncertainties as to what special services a county includes make it difficult to make conclusions regarding total expected annual cost differences between optical scan ownership and touchscreen ownership. Therefore the final analysis looks at the changes for each county in expenditures per 1000 registered voters from the pre touch screen period to the post period. We used the average of 2003 and 2004 expenditures per 1000 registered voters divided by the average of the 2000 and 2001 expenditures per 1000 registered voters to determine the percentage change for each county. We then took the average of the percentage change for each of the 11 touchscreen counties and compared these to the average of the percentage change for each of the 22 optical scan counties. The statistical analysis showed that touchscreen counties had an average increase of 57.3% in per-capita cost versus a value of 16.7% as the average of per-capita increase among counties with optical scanners. The difference between these two averages is 40.6% (57.3% minus 16.7%). This indicates a 40.6% higher increase in expenses for touchscreen counties than for optical scanner counties. This is significant at a 95% confidence level. Chart 2 is a scatter plot of the percent change of the expenditures in each county per 1000 registered voters before and after the state mandated that every county use only electronic voting machines. A comparison of the expenditure changes for counties with optical scan in both periods (O/O) to those that bought them in 2002 (P/O) shows 6.9% higher increase for O/O counties than the P/O counties showing no savings by not changing.. CONCLUSION The annual increase for optical scanner cost may be due partly to inflation and partly to special demands by the State. The results from this study show that a county s buying touchscreens can increase their annual expenditures of the order of 57.3% and a county buying optical scanners can increase their expenditures of the order of 16.7%. Optical scanners have the further advantage of providing a voter verified paper ballot that can be used to audit the machine s data and for any needed independent recount. To match this auditing advantage of optical scanners, the present touch screen systems would require the county to purchase and maintain a large number of printers, an additional set of costs that would significantly increase the county s annual expenses. One factor that may explain why having touchscreens cost so much more than optical scanners is because the county has to own and maintain so many more machines. We estimate that one optical scanner can count handle six voter s votes a minute (or 360 per hour) as they are cast but because it takes a voter at least three minutes to vote with touchscreens; it would take at least 18 touchscreens to perform per hour as well as optical scanners. In order not to have huge waiting lines on Election Day, most counties buy at least 10 touchscreens per precinct. Thus while one optical scanner adequately serves a precinct, the precinct needs approximately ten times as many touchscreens in order not to have huge lines of voters waiting to vote. 2

30,000 CHART 1 Page 3 Average Expenditures per 1000 Registered Voters in Florida Counties, 2003/2004 Dollar Expenditure per 1000 Voters, Average 2003/2004 25,000 20,000 15,000 10,000 5,000 Touch Screen Optical Scanner 0 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000 Number of Registered Voters, Average 2003/2004

120% CHART 2 Page 4 Change of Election Expenditures per 1000 Registered Voters in Florida Counties from 2000/2001 Average to 2003/2004 Average for Each County 100% Percent Increase in Expenditures per 1000 Registered Voters from 2000/2001 Average to 2003/2004 Average for Each County 80% 60% 40% 20% 0% -20% 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 Touch Screen Optical Scanner -40% Number of Registered Voters, Average 2003-2004 [Page 4]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 44 A B C D E F G H I J K Analysis of Data for Florida Election Expenditures Study Ave. Exp./1000 Section 1 Complete Data Ave. '03-'04 Ave. '03-'04 Exp. '03-'04/ voters change Ave. '00-'01 Ave. '00-'01 Exp. '00-'01/ County 1999 System Type* 2002 System # voters Expenditures 1,000 Vtrs in $ 03-'04/'00-'01 # voters Expenditures 1,000 Vtrs in $ Okeechobee Optical Scan O/O Optical Scan 17,591 311,783 17,725 11.65% 17,128 271,892 15,875 Flagler Optical scan O/O Optical scan 43,118 436,713 10,128-1.71% 34,240 352,836 10,305 Citrus Optical scan O/O Optical scan 86,409 794,123 9,190 20.63% 80,592 613,974 7,618 Bay Optical scan O/O Optical scan 93,799 817,695 8,718 18.76% 95,846 703,542 7,340 Clay Optical scan O/O Optical scan 96,408 1,152,973 11,959 27.03% 84,361 794,214 9,415 St John Optical scan O/O Optical scan 101,816 1,041,702 10,231 17.19% 88,258 770,522 8,730 Okaloosa Optical scan O/O Optical scan 120,674 1,121,262 9,292 16.75% 113,616 904,208 7,958 Alachua Optical scan O/O Optical scan 129,170 1,178,672 9,125 18.38% 120,005 925,039 7,708 Leon Optical scan O/O Optical scan 151,506 1,796,887 11,860 57.56% 147,451 1,109,945 7,528 Escambia Optical scan O/O Optical scan 176,817 1,740,157 9,842 13.36% 173,129 1,503,043 8,682 Manatee Optical scan O/O Optical scan 185,033 1,455,652 7,867 9.87% 159,408 1,141,420 7,160 Volusia Optical scan O/O Optical scan 288,805 2,525,418 8,744 25.53% 254,065 1,769,823 6,966 Orange Optical scan O/O Optical scan 432,945 5,692,856 13,149 19.11% 382,138 4,218,509 11,039 Jefferson Punch card P/O Optical scan 8,937 157,589 17,633-7.04% 7,961 150,998 18,968 Gulf Punch card P/O Optical scan 9,356 199,438 21,318 20.70% 9,862 174,176 17,661 Walton Lever machines P/O Optical scan 30,991 441,805 14,256-29.30% 28,814 581,029 20,165 Columbia Punch card P/O Optical scan 33,541 436,368 13,010 12.74% 31,674 365,506 11,540 Highlands punch card P/O Optical scan 59,247 481,839 8,133 19.88% 53,394 362,233 6,784 Hernando Punch card P/O Optical scan 107,772 832,271 7,723 30.69% 97,372 575,354 5,909 Osceola Punch card P/O Optical scan 117,108 1,798,435 15,357 7.12% 90,538 1,297,933 14,336 Marion Punch card P/O Optical scan 175,683 1,308,219 7,446 64.08% 146,312 664,026 4,538 Polk Punch card P/O Optical scan 283,032 2,335,256 8,251-5.92% 244,414 2,143,605 8,770 Lake Optical scan O/T Touchscreen 148,945 1,147,552 7,705 20.24% 134,007 858,702 6,408 Sumter Punch card P/T Touchscreen 38,023 947,370 24,916 55.72% 32,009 512,169 16,001 Indian river Punch card P/T Touchscreen 77,468 999,450 12,902 39.82% 71,868 663,132 9,227 Charlotte Punch card P/T Touchscreen 108,821 1,251,019 11,496 54.33% 99,256 739,344 7,449 Sarasota Punch card P/T Touchscreen 233,005 2,929,420 12,572 57.97% 220,246 1,752,829 7,959 Lee Punch card P/T Touchscreen 291,948 3,440,887 11,786 45.53% 248,847 2,015,264 8,098 Hillsborough Punch card P/T Touchscreen 569,575 5,137,388 9,020 61.97% 503,939 2,806,250 5,569 Pinellas Punch card P/T Touchscreen 572,858 5,129,234 8,954 33.83% 570,970 3,820,141 6,691 Palm Beach Punch card P/T Touchscreen 722,820 6,202,863 8,581 100.97% 663,036 2,831,115 4,270 Miami-Dade Punch card P/T Touchscreen 968,296 15,040,000 15,532 94.00% 892,174 7,143,000 8,006 Broward Punch card P/T Touchscreen 979,747 8,423,192 8,597 66.45% 903,452 4,666,420 5,165 Average Change in Exp. per 1000 voters 16.7% Post 2002 Opt. Scan Counties All * O/O=Optical Scan before 2002 and After 2002 57.3% Post 2002 Touchscreen Counties *P/O=Punch Card before 2002 and Optical Scan after 2002 *P/T=Punch Card before 2002 and Touchscreen after 2002 19.5% Post 2002 Opt.Scan Counties O/O 12.6% Post 2002 Opt. Scan Counties P/O Page 5

LETTER SENT TO EACH SUPERVISOR OF ELECTIONS IN EACH FLORIDA COUNTY Name of Supervisor of Elections April 5, 2005 Name of County I am working with a group that is doing a study of the election costs for different types of voting systems. I am interested in the total annual yearly expenditures for the Supervisor of Elections office and in the changes in the size of the registered voting population. I also want to know what types of voting system were used in the years 1999 through 2004. I will be delighted to share with you the results of this county by county study. Voting Systems. Data needed: 1. What type of voting system did you use in 1999?... 2. Did you change to an electronic system after 1999?...If yes, then: A. What type of system did you purchase?... B. Cost per machine?... C. How many machines did you buy?... D. When did you purchase them?... E. Was the cost paid by the commissioners directly or did it come out of the Supervisor of Elections budget... 3. Number of precincts in the county... 4. Number of registered voters in the years: A. 1999 (as of September 30th)... B. 2000 (as of September 30th)... C. 2001 (September 30th )... D. 2002 (as of September 30th)... E. 2003 (as of September 30th)... F. 2004 (as of September 30th)... 5. The data from the annual report of the county s independent auditors for the General Fund Schedule of Revenues, Expenditures and Changes in Fund Balance budget and Actual for the years 1999, 2000, 2001, 2001, 2003, 2004. I do not know if this is the exact title used by your auditors for their annual report to the Supervisor of Elections. The data needed from your auditor s annual report for the above listed six years is called in the report that I have from one county: total expenditures of the general government (for supervisor of elections office). It is subdivided into Personal services, Operating expenditures and Capital outlay. I would be happy to pay whatever cost is entailed in Xeroxing this data. I do not need the entire yearly auditor s report, just the page with the Total expenditures for each of the above listed six years. I look forward to hearing from you. Please let me know if there are any problems. If not, please mail the data to me at the above address. Thank you so much for helping in this research project. Page 6

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 B C D E F G H I J K L Statistics 1 TouchScreen? CostPerVoterIncrease REGRESSION RANGES: 0 11.65% 0-1.71% Y range = C2:C34 0 20.63% X range = B2:B34 0 18.76% 0 27.03% 0 17.19% 0 16.75% SUMMARY OUTPUT 0 18.38% 0 57.56% Regression Statistics 0 13.36% Multiple R 0.683761516 0 9.87% R Square 0.46752981 0 25.53% Adjusted R Square 0.450353352 0 19.11% Standard Error 0.211071619 0-7.04% Observations 33 0 20.70% 0-29.30% ANOVA 0 12.74% df SS MS F Significance F 0 19.88% Regression 1 1.212649759 1.212649759 27.21922163 1.152E-05 0 30.69% Residual 31 1.38108808 0.044551228 0 7.12% Total 32 2.593737839 0 64.08% 0-5.92% Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 1 55.72% Intercept 0.167 0.045 3.708 0.000817 0.075 0.259 1 39.82% X Variable 1 0.407 0.078 5.217 0.000012 0.248 0.566 1 54.33% 1 20.24% 1 57.97% 40.7% (above coefficients expressed as percentages) 24.8% 56.6% 1 45.53% Here 40.7% is our estimate of the extra percentage cost-per-voter increase for counties switching to touchscreen systems. 1 61.97% The 95%-confidence interval for this estimated extra-increase has a lower bound of 25% and upper bound of 57%. 1 33.83% The low p-value (0.000012) indicates very high confidence for our finding that TouchScreen has a higher cost increase. 1 100.97% 1 94.00% 1 66.45% Average Change in Expenditures per 1000 voter 16.68% Post 2002 Optical Scan Counties 57.35% Post 2002 Touchscreen Counties Page 7 40.66% Difference (same as "X Variable 1" Coefficient above in cell E22).