Dr. Shiva is a smart guy, but I disagree with his analysis. As best I can tell, the way he set up his data, dipping below the line does NOT mean fewer Trump votes, since "straight party" Republican votes are all Trump votes too. If you chart (Trump only votes as a percent of total any-candidate-only) as the Y and (straight Repub as a percent of total straight-party) as the X, you get a nice linear fit that goes from bottom left to top right as expected - i.e. the more Republican-straight-ticket as a fraction of all straight ticket votes in the precinct, the higher the fraction of Trump only votes out of all some-candidate-only votes. I did find that it leaned toward straight ticket votes, i.e. the slope of my curve fit was like 0.85 instead of 1. However it seemed totally legit.
In addition, it is my opinion that he has it a little bit backwards here. WAYNE COUNTY IS HORRIBLY CORRUPT. We should expect that Detroit poll workers frequently threw Trump ballots in the trash. That's why Wayne County looks different. It barely has any recognizable Republican presence because they are a den of corruption and iniquity.
With all the above said, I agree 100% with Dr. Shiva's comments about how primitive our elections are, and how it would be an amazing and totally feasible improvement to publish the ballot image scans for public consumption. In one fell swoop that would eliminate the need for manual recounts - anybody could recount the ballots who wanted to.
Wouldn't you expect the % of total votes to Trump as % of Republican straight line increases? The point of the Dr. Shiva presentation is to the proportional decline as % of RSP increases. Right?
(percent of Trump-individual votes to the total of any-individual votes) as X
...against...
(percent of Republican-straight-ticket to the total of any-straight-ticket votes) as Y
... then you get a linear pattern that shows both increase together. It is angled favoring the straight ticket side a bit, but they definitely increase together. You can nicely curve fit a line with e.g. slope 0.85.
The reason Dr. Shiva's shows otherwise is that he subtracts the Republican straight ticket values from his Y values. This ends up exaggerating the lean toward straight ticket. He interprets that as fewer Trump votes, however I believe he is wrong to do so, because straight ticket Repub votes are also Trump votes. When he subtracts his X from his Y, he pretty much guarantees it has to dip below the line as it moves right.
This is potentially a very good point but I think we need to see the totals of each kind of vote for each graph before implying the conclusions are wrong.
Shiva's Y axis is (% of total Trump votes among votes given to a specific candidate - % of total Republican votes among down-ballot votes). My understanding is he's plotting this value because in a pro-Trump precinct, you would expect to see people vote Trump when they vote for any individual candidate (i.e. anything not strictly down-ballot), and when they vote down-ballot you would expect to see them vote Republican.
In the video he uses roughly equal numbers between the two types of votes and his explanation makes sense. If I was shown 1000 people and was told roughly 60% of them support Trump but was not told which of the two types of votes this entire group did, I would still expect roughly 600 of them to be of whatever kind of vote meant Trump; the type of vote doesn't necessarily factor in.
If you use pretty different vote totals, though, your assessment starts to make more sense. To use a ridiculous example for the sake of expediency, let's say in a precinct 100,000 people voted down-ballot and only 10 people voted individual. Well if I'm then told this is a heavily Republican precinct I'm going to expect most of those 10 individual votes to be for Biden since statistically speaking there are a lot more Republicans than Democrats in this area; so there's more likely to be an anti-Trump Republican in the mix than a pro-Trump Democrat or Independent due to the sheer number of Republicans. Using example numbers in this case, if 80% of down-ballots were Republican but only 50% (so 5) of the individual votes were Trump you'd see a deficit of 30%!
Of course it's possible that if such a case existed it would be considered an outlier die to the large discrepancy in voting type numbers and would be excluded from the analysis as an outlier. Once the number of individual votes starts matching the number of down-ballots, Shiva's math looks more sensible. Using the same example above except this time the vote type counts are more equal (heavy Republican precinct with say 50,000 down-ballot and 50,000 individual), I'm not expecting much deviation in the percentages because in this precinct neither type of voting is significantly more popular so a Republican is equally likely to vote Trump individually as they are to vote down-ballot. Seeing a 30% differential here is much more eyebrow-raising because that implies a stark difference in voting habits based on an otherwise completely arbitrary attribute of the vote.
My hunch would be that in real life, the types of votes are closer to being of similar quantities in each precinct, which is maybe why Shiva and his team didn't even bother to address this point in their video - it's a rare enough occurrence that it isn't worth discussing. This is all based on my assumptions though, seeing vote totals of each type alongside the graphs would certainly be good for clarification.
Dr. Shiva is a smart guy, but I disagree with his analysis. As best I can tell, the way he set up his data, dipping below the line does NOT mean fewer Trump votes, since "straight party" Republican votes are all Trump votes too. If you chart (Trump only votes as a percent of total any-candidate-only) as the Y and (straight Repub as a percent of total straight-party) as the X, you get a nice linear fit that goes from bottom left to top right as expected - i.e. the more Republican-straight-ticket as a fraction of all straight ticket votes in the precinct, the higher the fraction of Trump only votes out of all some-candidate-only votes. I did find that it leaned toward straight ticket votes, i.e. the slope of my curve fit was like 0.85 instead of 1. However it seemed totally legit.
In addition, it is my opinion that he has it a little bit backwards here. WAYNE COUNTY IS HORRIBLY CORRUPT. We should expect that Detroit poll workers frequently threw Trump ballots in the trash. That's why Wayne County looks different. It barely has any recognizable Republican presence because they are a den of corruption and iniquity.
With all the above said, I agree 100% with Dr. Shiva's comments about how primitive our elections are, and how it would be an amazing and totally feasible improvement to publish the ballot image scans for public consumption. In one fell swoop that would eliminate the need for manual recounts - anybody could recount the ballots who wanted to.
Wouldn't you expect the % of total votes to Trump as % of Republican straight line increases? The point of the Dr. Shiva presentation is to the proportional decline as % of RSP increases. Right?
If you plot...
(percent of Trump-individual votes to the total of any-individual votes) as X
...against...
(percent of Republican-straight-ticket to the total of any-straight-ticket votes) as Y
... then you get a linear pattern that shows both increase together. It is angled favoring the straight ticket side a bit, but they definitely increase together. You can nicely curve fit a line with e.g. slope 0.85.
The reason Dr. Shiva's shows otherwise is that he subtracts the Republican straight ticket values from his Y values. This ends up exaggerating the lean toward straight ticket. He interprets that as fewer Trump votes, however I believe he is wrong to do so, because straight ticket Repub votes are also Trump votes. When he subtracts his X from his Y, he pretty much guarantees it has to dip below the line as it moves right.
This is potentially a very good point but I think we need to see the totals of each kind of vote for each graph before implying the conclusions are wrong.
Shiva's Y axis is (% of total Trump votes among votes given to a specific candidate - % of total Republican votes among down-ballot votes). My understanding is he's plotting this value because in a pro-Trump precinct, you would expect to see people vote Trump when they vote for any individual candidate (i.e. anything not strictly down-ballot), and when they vote down-ballot you would expect to see them vote Republican.
In the video he uses roughly equal numbers between the two types of votes and his explanation makes sense. If I was shown 1000 people and was told roughly 60% of them support Trump but was not told which of the two types of votes this entire group did, I would still expect roughly 600 of them to be of whatever kind of vote meant Trump; the type of vote doesn't necessarily factor in.
If you use pretty different vote totals, though, your assessment starts to make more sense. To use a ridiculous example for the sake of expediency, let's say in a precinct 100,000 people voted down-ballot and only 10 people voted individual. Well if I'm then told this is a heavily Republican precinct I'm going to expect most of those 10 individual votes to be for Biden since statistically speaking there are a lot more Republicans than Democrats in this area; so there's more likely to be an anti-Trump Republican in the mix than a pro-Trump Democrat or Independent due to the sheer number of Republicans. Using example numbers in this case, if 80% of down-ballots were Republican but only 50% (so 5) of the individual votes were Trump you'd see a deficit of 30%!
Of course it's possible that if such a case existed it would be considered an outlier die to the large discrepancy in voting type numbers and would be excluded from the analysis as an outlier. Once the number of individual votes starts matching the number of down-ballots, Shiva's math looks more sensible. Using the same example above except this time the vote type counts are more equal (heavy Republican precinct with say 50,000 down-ballot and 50,000 individual), I'm not expecting much deviation in the percentages because in this precinct neither type of voting is significantly more popular so a Republican is equally likely to vote Trump individually as they are to vote down-ballot. Seeing a 30% differential here is much more eyebrow-raising because that implies a stark difference in voting habits based on an otherwise completely arbitrary attribute of the vote.
My hunch would be that in real life, the types of votes are closer to being of similar quantities in each precinct, which is maybe why Shiva and his team didn't even bother to address this point in their video - it's a rare enough occurrence that it isn't worth discussing. This is all based on my assumptions though, seeing vote totals of each type alongside the graphs would certainly be good for clarification.