Comments by "whyamimrpink78" (@whyamimrpink78) on "CNN"
channel.
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
Arshan, sorry for the late reply, I do have responsibilities.
Bernie misrepresented the study by claiming medicare for all would save the American people money. That is not what the study concludes. Bernie made that conclusion by pointing to the $32 trillion over 10 years the study published. Bernie did a grossly oversimplification presentation with that number and compared it to what we pay now and said we will save money. However, you have to see what that $32 trillion over 10 years actually is.
To start, that number is just for public spending, it does not include private which will still exist even with medicare for all. Bernie using what we pay now includes both private and public. Next, that $32 trillion was the lower bound. They found a range of numbers but published the lower bound. Chances are the cost will be higher. They also made assumptions based on Bernie's numbers that are most likely not going to happen. For example, they are saying that despite increasing demand prices will not go up which is an economic fallacy. Also, they are saying that health providers will be willing to take 40% less money, that is based on Bernie's numbers. That is unrealistic unless quality goes down or you do some sort of tort reform because doctors and hospitals pay a lot in liability insurance to protect against malpractice lawsuits.
Overall, that $32 trillion
1. Does not include private care cost
2. Was a conservative estimate
3. Made many assumptions that economically will not happen
Bernie compare that number to
1. A number that includes both public and private cost
2. He did not give the full details about the study
In the end Bernie is misrepresenting the study because Bernie is a corrupt, career politician. He doesn't care about actually discussing the issues and progressing our country, he only cares about keeping his seat in office.
1
-
1
-
1
-
@pidayrocks2235 the 80 million case is a stretch, but it is based on antibody testing out of NY, Santa Clara and USC where more people than expected had the antibody. That suggests many were infected without knowing it.
As for statistics, I just made a remark to someone else how, with your method, you are saying that those who die with the virus is purely because of the virus and thus there is a 17% mortality rate. However, there are comorbitities in that almost all who died have other health issues. Thus, the proper way is to weigh out to what degree the virus plays a role. For example, if someone had heart disease, diabetes, and the virus and the virus is listed as 3rd in cause of death and heart disease was number one, the proper way would bee to say, and just giving a number, that the virus contributed 20% to the person's death where 50% was from hear disease and 30% was from diabetes. The issue is that no one know to what degree the virus plays a role because one, we do not have a control, and two, the data set is low. As I pointed out in the example of number of people dying due to lack of healthcare access, that number ranges from essentially zero to 60,000 a year. But again, those people are sick to begin with.
In the book "Being Mortal" the author writes how people seek out modern medicine to live another 5 or 10 years but will really live only 5 or 10 months. That is because people in that case who die have many issues. So with this virus, basically all who died were old and/or sick to begin with. So their chances of dying in a few months was high to begin with.
As for upper and lower bounds, you are throwing out words you do not understand. That is basically a function of the math. No different than an average and a standard deviation. You can have an average with a low SD with a small data set. And you can have an average with a higher SD with a larger data set. What is more accurate? Many will argue the larger data set.
In the Scientific American article entitled
"How can a poll of only 1,004 Americans represent 260 million people with only a 3 percent margin of error?"
Prof. Andrew Gelman writes
"The margin of error is a mathematical abstraction, and there are a number of reasons why actual errors in surveys are larger."
Basically, it falls from the math which is why a lot of times end results differ greater than the polls. Same with what you are throwing out. A lot of numbers in stats are mathematical abstractions. A famous book is "How to Lie with Statistics". Basically, people can do legit analysis on any stat and come up with varying conclusions.
Bottom line, 100,000 is a small sample size for something this complex. And you claim I do not understand statistics?
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
@sagisli the country is not leading the world in infections and deaths when you take population into account. Nations with more deaths per million, San Marino, Andorra, Spain, Belgium, Italy France, etc. There are several in front of the US. That is even with us over stating the numbers (such as someone with coronavirus dies is listed as a coronavirus death even if the cause was coronavirus or not).
Trump did well, he let the states handle it. The reason why is because every state is experiencing this issue differently. Most of the cases/deaths in the US are in the New England area such as Connecticut, NY, NJ, etc. Newsome is just lucky he is in an area that was not hit hard.
Also, there is evidence to suggest that the early flu season in CA was actually the virus. Thus people in CA already experienced the virus and built up an immunity.
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1
-
1