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Well Trump made plenty of ventilators if needs be 😂😂😂😂
If Biden is such a great candidate, why does his campaign hide him in the basement? Why did he turn down additional opportunities to debate President Trump, allowing voters to better understand the policies of both candidates prior to early voting? If the Biden message and vision for America is that great, why wouldn’t democrats want to see more not less?
Everyone that’s seen the film is saying it is worse than you can imagine. They are sick to their stomach and cancel netflix right after. It’s just awful you’re forced to have it in your library. CANCEL!
They are showing a Biden lead so people won’t question it when they try to steal it after.
This part was EPIC!
vegas protester clocked by trump supporter
Why are the liberal all upset at this? 99.7%? That’s nearly everyone – and why put our census workers at risk when that rate is similar to prior years.
Oh good lord – yes, I’m familiar with autocomplete. There are several reasons it may not appear. First, showing up on autocomplete takes some time. Google has to determine programmatically if an autocomplete recommendation is a good fit. Meaning, it correctly guesses user intent based on a sub-string of words. It’s only shown to a limited number of people at first until conclusive data can be reached. Since it is a recently tending term, it may be in that state. The 2nd reason is also likely to influence this situation. Google does not make recommendations to certain classes of searched. For example if you do a name, +identifying information there will not be autocomplete. Due to them not wanting to bias search results by providing information related to voting, certain voting queries might be ineligible. I don’t know the specifics of this situation. I’m sure google has a help file that would list more situations in which a search term would not trigger autocomplete. But, just because it’s not appearing doesn’t mean the search term isn’t happening. There are many other reasons.
We thank you for your utmost integrity!!!!!
Live export, direct from FL
So there are some nuances. A keyword is not a search term. A keyword is a grouping of search terms triggered from a set keyword. For example, KW ‘toy’ would include search terms ‘toy boat’, toy car, etc. different keywords can trigger the same search term so it’s somewhat messy data. 2) the data in the kw planner is delayed. Not real time. You will not see last weeks numbers until someone in November.
Larger advertisers have access to search term data and the terms’ attributes such as number of times a search query was made.
They can import direct from Google into a google cloud service called big query (database query not search query). Then analyze.
I can tell you enough people have searched to change their vote, that if 10% actually change their vote it would be enough to flip some states based on last years results.
We have an NDA and cannot reveal search term data explicitly. Obviously this is guarded data.
Have a nice day. But it is great that you are getting closer to the level of analysis we do.
Because I have access to Google Ad tools and can see actual numbers. It’s not insignificant. Far from it. Have a nice day.
When you thought you seen it all—lol!
Google doesn’t reveal the number of searches. It’s indexed on a scale of 1-100. It hit 100. Since the average trending indexed number is 3, the day it started strongly trending was 33% the normal trend. Your reply shows how low information you are. Google explains on their site the index. No wonder you are voting for Biden. He did say today something to the effect he didn’t like smart guys. Maybe he meant it in a literal sense. Go, and blindly follow your leader in ignorance.
wow! you’re right the trailer on youtube has 2 million DISLIKES.
I wrote the reply in your other comment. Sorry!
I’m making a narrow point in the article.
1) That the overall death rate for all deaths is one of the lowest it’s ever been and not giving any specific reason.
2) That it’s surprising the death rate is so low being in a national pandemic emergency.
My only recommendation from this, at the very least is this:
At the very least, this data shows we need to analyze COVID-19 deaths in the context of the broader U.S. mortality rate from all causes. It appears normal deaths are being attributed to COVID-19 if the patient is COVID-19+, even if another underlying chronic cause is responsible.
We need to get a clear definition of what constitutes a COVID-19 death. Right now states and countries can really attribute anything if the patient is COVID-19+. But based on the antibodies test from Santa Clara, CA… COVID-19 is even more prevalent that previously thought. So there is ample crossover between what caused the death.
I’m really just asking for a standard definition everyone use. Once we have that and have the data behind that, we can make more conclusions. But with very weak and siloed data, it’s hard to make a lot of conclusions.
CRUDE DEATH RATE is the total number of deaths to residents from any cause in a specified geographic area (country, state, county, etc.) divided by the total population for the same geographic area (for a specified time period, usually a calendar year) and multiplied by 100,000. It has nothing to do with crude oil.
I don’t disregard any deaths. I’m looking at crude mortality (from each and every cause):
CRUDE DEATH RATE is the total number of deaths to residents in a specified geographic area (country, state, county, etc.) divided by the total population for the same geographic area (for a specified time period, usually a calendar year) and multiplied by 100,000.
Yes, agree. To lessen the variance caused by early data not being as accurate, I don’t use the latest data set. I wait two weeks which is why we only show data until April 5th.
By far the biggest errors come from the most recent ‘full’ week of data. That’s why I ignore data from week 15 and week 16; and don’t include it.
A 10% error rate to week 14 in the direction of the most likely revision (upwards) would be 54,000 — which is still lower than all periods of increased influenza deaths. 10% would be an extreme revision considering I’m already using 2 week old data to attempt to keep the data as accurate as possible. In any case, each week the CDC updates, I update the entire data set, and will call out any remarkable revisions.
However, if you look at the most recent full sets (week 9-11), the standard adjustment after labeled 100% complete by the CDC is only 4-6%. So we’re looking at about a 5% upward revision which doesn’t change the conclusions that 1) mortality is very low for a national pandemic emergency and 2) we need further research on what constitutes a covid-19 death.
Furthermore, the Sweden data (they did not lock-down) is starting to challenge more assumptions.
The ultimate conclusion here is we need to take a step back, look at more data points and revisit some of our base assumptions as the entirety of data isn’t matching up with the current mainstream conclusions/assumptions.
I only use complete data. The CDC publishes how complete a set is. Notice I’m only using week 14 in this set. There is actually data for week 16, but week 15/16 are incomplete. I wait until the complete data set filters in and the CDC confirms it’s 100% in from all districts. After the CDC labels data 100%, there are still revisions. But, the recent historical revisions are less than 5% after two weeks.
So, yes, even before I read the post you shared… I identified the same exact issue and accounted for it in the presentation of data.
Dr. Spencer’s data model is a bit flawed. He’s using a 5-year historical average. Whenever you do a data model, you need to weight the model, at a disproportional ratio, to recent-data trends. He doesn’t do that. As it turns out, with all the attention on COVID-19, epidemiological data is being reported at a much quicker rate than the 5-year historical model suggests. We are getting more complete data quicker.
Think about it- if it was your job to provide data that the world needs, wouldn’t you devote more resources to providing it quicker? That’s what’s happening.
I work with trillions of data points, across billions of auctions a day. Identifying trends and patterns is my livelihood.
My only conclusions are this:
1) we need to do a better job at defining certain data points
a) covid -19 deaths: when do we attribute to pre-existing chronic conditions or covid-19 itself? or do we categorically assign death: covid-19 alone or covid 19 w/ pre-existing condition when looking at the death rate? uniformity will help analyze this data in aggregate.
b) death rate to DETECTED covid-19 cases is not really a metric. every state/country detects covid-19 using different methods and thus different rates are attributed to that method rather that qualities of the virus itself.
2) i find it quit surprising that in the midst of a national pandemic emergency, that stops a multi-trillion dollar economy, the chances of dying from any cause are at the lowest levels across multiple years. we deserve proper data as listed in point (1) given how the lock down effects businesses, and the livelihood of billions.
Ultimately, I’m looking for truth and am suggesting areas of further research based on surprising crude mortality rate data.
The data is emerging that we did not need to lock down. Sweden did not lock down, and the mortality rate there is lower than france and italy.
Sweden is currently higher than most Scandinavian nations. But since they did not lock-down, they likely hit herd immunity quicker, and will have lesser deaths down the road. While the other Scandinavian nations, when they come out of lock down, may have an increase in deaths since they are not as far along in establishing herd immunity.
Furthermore, Sweden’s economy not taking a slug to the face with a baseball bat, as other nations.
Thought experiment: If we could reduce automobile accident deaths to virtually 0 by reducing the speed limit to 15 mph, should we do it?
Yes, use that link and then click the green “download” button. In the download, you’ll get a CSV. Among the many columns, there are three columns that list deaths:
NUM INFLUENZA DEATHS, NUM PNEUMONIA DEATHS, TOTAL DEATHS
-The first one is just flu
-The second one is just pneumonia
-The third one, total deaths, is crude deaths (all causes)
I verified the crude number of deaths by taking the sum of the all cause and matching it to the number of deaths in a year in the us. For example, it’s about 2.7 million total deaths in all of 2015 in USA from all causes. That matches the total deaths this data set has for 2015 (if you add up total deaths per week).
Next, the crude death rate was calculating taking the number of deaths per week divided by the population of the us in that specific year and then multiply that number by 100,000. (Standard crude mortality formula).
I couldn’t find a data set of weekly US deaths anywhere but this site. But the total deaths represent all deaths, and is included with pneumonia and influenza deaths it appears to add perspective.