R help - Nov 2020 - analyzing results from Tuesday's US elections

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...

???? 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...

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.

Matthew

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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