[R] analyzing results from Tuesday's US elections

Matthew McCormack mccorm@ck @end|ng |rom mo|b|o@mgh@h@rv@rd@edu
Tue Nov 17 07:59:37 CET 2020

Bye the way, I thought I had checked my e-mail before sending it, but my 
last e-mail had an unfortunate typo with an 'I' that originally belonged 
to the beginning of a deleted sentence.


On 11/17/20 1:54 AM, Matthew McCormack wrote:
> External Email - Use Caution
>      No reason to apologize. It's a timely and very interesting topic 
> that provides a glimpse into the application of statistics in 
> forensics. I had never heard of Benford's Law before and I think it is 
> really fascinating. One of those very counter intuitive rules that 
> show up in statistics and probability; like the Monty Hall problem. 
> Why in the world does Benford's Law work ?  I have been wondering if 
> it could in any way be applied to biological data analysis. (Also, I 
> discovered Stand-up-maths !).
>    Often things are not as easy to figure out as we may first 
> estimate. I think you would have to start with how you would envision 
> a fraud to be committed and then figure out if there is a statistical 
> analysis that could detect it, or develop an anlalysis. For example, 
> if a voting machine were weighting votes and giving 8/10ths of a vote 
> to 'yes' and 10/10ths vote to a 'no'. Is there some statistical 
> analysis that could detect this ?  I, Or if someone dumped a couple of 
> thousand fraudulent ballots in a vote counting center, is there some 
> statistical analysis that could detect this ?  Who knows, maybe a 
> whole new field waiting to be explored. A oncee-in-a-while dive into a 
> practical application of statistics that has current interest can be 
> fun and enlightening for those interested.
> Matthew
> On 11/16/20 9:01 PM, Abby Spurdle wrote:
>>          External Email - Use Caution
>> I've come to the conclusion this whole thing was a waste of time.
>> This is after evaluating much of the relevant information.
>> The main problem is a large number of red herrings (some in the data,
>> some in the context), leading pointless data analysis and pointless
>> data collection.
>> It's unlikely that sophisticated software, or sophisticated
>> statistical modelling tools will make any difference.
>> Although pretty plots, and pretty web-graphics are achievable.
>> Sorry list, for encouraging this discussion...
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