Research Methodology, pdf - 2B2B.org
Research Methodology, pdf - 2B2B.org
Research Methodology, pdf - 2B2B.org
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I'll look up the exact source and quote later to give you but in my readings about voting<br />
efficiency one <strong>org</strong>anization estimated that the lost votes during the 2000 U.S. presidential<br />
election could have been up to 2 million votes -- not exactly a precise accounting feat.<br />
--<br />
second letter:<br />
The estimate of lost votes during the 2000 U.S. presidential election was four to six million, not<br />
two million as I had previously written.<br />
Here's the quote taken from Where to Now for E-Voting?:<br />
"Amongst other problems, The CalTech/MIT Voting Technology Project estimated some four to<br />
six<br />
million votes were lost in 2000 due to ballot, equipment, registration or polling-place problems.<br />
In<br />
response, Americans clamoured for new voting technology to replace the ageing machines<br />
peppering<br />
US polling booths across the nation." (Bushell, 2003).<br />
Even though we perhaps put too much weight on to brand name dependence, I think most people<br />
would agree that MIT and CalTech are prestigiously reputable outfits and would trust their<br />
research results. However, since the 4 to 6 million figure seems to be such an outrageously outof-bounds<br />
and unexpected estimate, that's the sort of information that, if someone were to write<br />
an official report on the state of online voting, they would want to examine by looking up the<br />
research methodology of that particular project (perhaps by contacting the authors of the research<br />
project) to determine how those figures were deduced.<br />
References:<br />
Bushell, Sue. (2003). Where to Now for E-Voting? Retrieved Oct. 24, 2003 from<br />
http://www.cio.com.au/<br />
index.php?id=405941257&eid=-601<br />
from U6D2 from Jan concepts related to data collection and analysis<br />
Descriptive observational variable<br />
inferential observational variables<br />
evaluative observational variables<br />
criterior related observer reliability<br />
intra-observer reliability<br />
inter-observer reliability<br />
observer drift<br />
reliability decay