Welcome to the week of classical posts on global warming, now “climate change”, a subject which I had hoped had faded into obscurity, but, alas, has not.
I was involved for a time with a group of physicians seeking to created a trusted peer group using block chain technology to evaluate peer reviewed research using the many of the analysis methods Mr Briggs employs. The effort was driven by the total failure of the CDC and other “experts” during the COVID scamdemic. The group never got off the ground. Apparently too few physicians want to know the real truth, or don’t value knowing it enough. My question for Mann and his cohorts is do they not know they’re using such poor data manipulation methods, or do they know and not care? Either way, such methods disqualify them as “experts” the world should listen to. And if they know and do not care, that means that someone, somewhere is paying them (or blackmailing) to sacrifice their scientific reputations. I pray they never enjoy another night’s restful sleep or untroubled look in the mirror.
The statistician drowned in a river that averaged 2 feet deep! I was taught in school many years ago that means are meaningless without an accompanying statement of deviation from the mean using the actual data. In geologic data, an average cuts out the data that is most meaningful. It is the data that does not fit the average that either exposes risk or provides opportunity.
Almost every day this summer we hear stories that this is the hottest summer on record through out the world. My data point in middle America does not correlate to that whatsoever. This has been one of the mildest summers that I can remember. Color me skeptical on the talking heads data
It doesn't matter what you do if the "data" is bogus. When the paradigm is "if you don't like the results we will get different numbers".
By arguing about the analysis, you validate the basis, when in truth, the basis is a lie. I know it is a lie, you know it is a lie, they know it is a lie and the people who pay them to lie know that it is a lie.
Like the BS about "covid" there is no point in talking about it because there is no possible way that the numbers can be known. The tests were bogus, the reports were bogus, everyone was paid (huge amounts of money) to lie about the numbers. Like AIDS, the bigger the number, the more you were paid.
So there can be NO rational discussion about Covid, or climate or CO2 because there simply is no data available.
But if you want to be published and offered tenure or degrees or anything you have to perpetuate the nonsense or be too stupid to recognise that you are too stupid to know what the heck you are talking about.
What about smoothing daily timeseries with a bidirectional period of 3 in order to get weekly data, since reporting behaviour often varies considerably between days of the week?
I am currently doing this to correlate various COVID variables with each other. It's the absolute minimum period that will take care of the issue. Hospitals aren't as busy on weekends as they are on weekdays and the same goes for vaccination centers, sequencing labs etc.
I was involved for a time with a group of physicians seeking to created a trusted peer group using block chain technology to evaluate peer reviewed research using the many of the analysis methods Mr Briggs employs. The effort was driven by the total failure of the CDC and other “experts” during the COVID scamdemic. The group never got off the ground. Apparently too few physicians want to know the real truth, or don’t value knowing it enough. My question for Mann and his cohorts is do they not know they’re using such poor data manipulation methods, or do they know and not care? Either way, such methods disqualify them as “experts” the world should listen to. And if they know and do not care, that means that someone, somewhere is paying them (or blackmailing) to sacrifice their scientific reputations. I pray they never enjoy another night’s restful sleep or untroubled look in the mirror.
Well, based on the various lawsuits Mr. Mann has filed, I suspect he knows, and doesn't care.
The statistician drowned in a river that averaged 2 feet deep! I was taught in school many years ago that means are meaningless without an accompanying statement of deviation from the mean using the actual data. In geologic data, an average cuts out the data that is most meaningful. It is the data that does not fit the average that either exposes risk or provides opportunity.
Almost every day this summer we hear stories that this is the hottest summer on record through out the world. My data point in middle America does not correlate to that whatsoever. This has been one of the mildest summers that I can remember. Color me skeptical on the talking heads data
Same here in Europe. They say hottest summer while barely one week was so far hot and many evenings had to wear sweatshirt...
Come on man!
It doesn't matter what you do if the "data" is bogus. When the paradigm is "if you don't like the results we will get different numbers".
By arguing about the analysis, you validate the basis, when in truth, the basis is a lie. I know it is a lie, you know it is a lie, they know it is a lie and the people who pay them to lie know that it is a lie.
Like the BS about "covid" there is no point in talking about it because there is no possible way that the numbers can be known. The tests were bogus, the reports were bogus, everyone was paid (huge amounts of money) to lie about the numbers. Like AIDS, the bigger the number, the more you were paid.
So there can be NO rational discussion about Covid, or climate or CO2 because there simply is no data available.
But if you want to be published and offered tenure or degrees or anything you have to perpetuate the nonsense or be too stupid to recognise that you are too stupid to know what the heck you are talking about.
What about smoothing daily timeseries with a bidirectional period of 3 in order to get weekly data, since reporting behaviour often varies considerably between days of the week?
I am currently doing this to correlate various COVID variables with each other. It's the absolute minimum period that will take care of the issue. Hospitals aren't as busy on weekends as they are on weekdays and the same goes for vaccination centers, sequencing labs etc.