Wuhan Coronavirus - COVID-19 Analysis & Summary - This is not just fucking pneumonia. It is everything but the kitchen sink. Lungs, heart, kidneys, liver, brain, blood vessels, testes. It affects them all.

Oh calipers? Really?
How about this?
View attachment 1222382


Because this is what you've been experiencing, getting assblastered for the amount of autistic drivel and doomer sperging, wrapped up in your lack of understanding of basically everything and severe autism.

In the case of the instruments description, you need 2 of these. One for lying, the other for being a massive doomer faggot.
Except he might enjoy it...
 
Using the shitty incomplete data I currently have, I tried to see what a regression model would look like, if I want to use death toll to predict total cases.
Dataset is incomplete. Had better things to do today.

The WHO data is absolutely shit. Hey David Clop, this is how you actually do stats.

1586459431167.png

So let's see, I have an R-sq of 95.97%! If I were David Clop, I would think my model is good.

So is the data Normal?
What we want to see:
- dots following the line
1586459485789.png

Hmmm, it looks shit to me. Let's do an Anderson-Darling test.
1586459774125.png

So the P-value is as small as David Clop's brain. Null hypothesis of normality is rejected.
Basically, the data isn't fucking normal.

How about residual plots?
What we want to see:
- Nice, random spread
- No patterns
1586459520706.png

Yeah.

Note that these tests are always performed before making an actual model. If there's no even spread observed in the residual plots and if the data isn't normal, then this usually gives 2 options:
- Refine the model by adding in interaction terms, dummy variables, Log-transform... etc
- Non-linear test

So the conclusion is simple. Even though the R-sq is very high, the model is absolutely trash.
All those so called economists with PhDs and what-not would have reached the same conclusion, but they didn't. Decided to conspire about numbers being made in a spreadsheet. Then doomer faggots like David Clop eats this information up without knowing what he's talking about. At this point, the credentials of all these faggots people bring up must be questioned.
I did the same for China of course, same shit results. Of course what I'm doing is a little more involved than fitting a curve over several dots in Excel.
1586460192805.png

(Large R-sq, but shit model)

I'll complete the data if I'm bothered and work with the numbers to get a better model.
The better model might have a far lower R-sq, which is what I've stated previously. Low R-sq but good model. This post illustrates a case where R-sq is very high but the model is shit.

Let's quote David Clop here:
I have never lied about COVID-19. Never. Not even once.

Everything I have stated about this virus is the truth as I understand it. I take this very seriously.
I am many things. A liar is not one of them. You are accusing me of dishonesty, when you have absolutely no proof that anything I've said about this virus is a lie.

I claim that COVID-19 is a multi-systemic disease that affects almost all of the vital organs. Lungs, heart, liver, kidneys, brain, and reproductive system.

I have numerous citations to back this up.

Where is your disproof?
Do we have a liar count here?

Like I said, I copied and pasted it out of Windows Calculator. It had that order of operations already.

I did think about bracketing it just to be sure, but I thought it was fairly unambiguous what I actually meant based on the sum, so I didn't bother.
No David, you're a faggot that can't do basic math. No matter what excuse you may conjure up, you get 0.
No idea how you got the archaic division sign by coping shit from a "Windows calculator". I tried but can't replicate the results, but then I don't actually use windows calculator.
 
I love how @Drain Todger is dredging up the exact stupid nonsense that I called out a month ago.

Hey, don't you know that the current mong line is 'it's time to get back to work!' and 'this is all China's fault (don't look at the fact that the Chinks warned the world in early Jan and Trump's CDC was still denying community transmission was a thing in late February)'?
 
I love how @Drain Todger is dredging up the exact stupid nonsense that I called out a month ago.

Hey, don't you know that the current mong line is 'it's time to get back to work!' and 'this is all China's fault (don't look at the fact that the Chinks warned the world in early Jan and Trump's CDC was still denying community transmission was a thing in late February)'?
Your autistic Iranian tier shitposting in the main thread gives Drain Todgers fart-huffing a run for its money. The only reason you are not in his situation is because you were not autistic enough to make your own thread (yet).
 
Your autistic Iranian tier shitposting in the main thread gives Drain Todgers fart-huffing a run for its money. The only reason you are not in his situation is because you were not autistic enough to make your own thread (yet).
Lol OK faggot. Are you going to keep pretending that the masters of the US government are delibrately engaging in actions to kill as many Iranians as possible?
 
What? You mean the non-peer-reviewed pre-prints? But this is a fast-moving situation. There hasn't been enough time for peer review on some of these things.



Well, to be quite honest, either way, I am happy to provide some entertainment in these trying times.

Many of us are locked indoors and basically going stir-crazy, so a little fun and diversion never hurt.

Your fundamental mistake is that you assume I lack self-awareness and do not realize both that I am a clown, and that clowns provide a valuable service.

Picture a version of Chris-chan who is just dimly self-aware enough to stew in perpetual torment, as in Harlan Ellison's I Have No Mouth, and I Must Scream. You would only begin to scratch the surface of what it's like to actually be me.

This.... is like teaching Chinese postgrads, and whoever handles induction for freshmen at your college should be assblasted for failing to insist on a mandatory course on citations and academic writing. That’s their fault, not yours. I will lead you through the basics and then you can Google-fu yourself a few basic guides from other colleges to keep as a reference.

It is setting students up to fail to assume that they all know how to write an academic paper, and it annoys me when institutions take your money and don’t give you the skills you need to succeed.

The first thing every academic paper has is a thesis. Yes, even your first year essays. If you approach your work from the beginning of your academic career correctly, the skills will quickly become second nature. All a thesis is, really, is a sentence or two outlining the proposition that your paper intends to prove (or disprove, but the negative thesis is best avoided in humanities if you can).

You then arrange about three to five main strands of argument that will support your thesis. You will discuss each of these in a seperate sub heading, or chapter. It isnt that important how you divide them, but as your reader I should be able to easily distinguish one argument from another. As you discuss each one, you should also pick up the major arguments against it, the major known issues with the analysis, and any areas of doubt/lack of info, and deal with each one. You aim to rebut any material that says “your argument is wrong”, and you aim to illustrate what information is missing and how it may be gathered in response to material that says “you just don’t have enough evidence to support this argument”.

If there seems to be a shitload of material that says you are wrong or that there’s no information to support your argument and you are just pulling it out of your ass, this is a strong signal to sit down, go back carefully through all the material you have, and reconsider your assumptions and the conclusions you’ve drawn from those. It’s absolutely fine to be wrong. But if you submit wrong stuff to me, I have to mark you accordingly. It’s fine to take a couple of hours to recheck your thinking.

Now, in order to support each of your arguments, you need academic work. (In medical sciences, you will need data unless you’re doing a Cochrane review. I haven’t written a science paper since high school, so I will leave it to the better educated than me in this thread to talk you through data handling skills.) You need what a much missed professor of mine used to call in fruity tones “ssscholarly aaaaarticles”. Some sources, as we all remember from our first ever history lesson at school, are better than others. This is because they are written by people who are more authoritative in the field; they were published in a leading journal that has stricter peer review standards; the authors don’t have obvious or declared notable conflicts of interest; the paper emits from academics appointed to a prestigious institution. These on their own are not infallible and none on their own will be enough. It is however true to say that the better ‘score’ an article gets by these metrics, the less complete bullshit it is likely to be compared to the work of I.M. Clown self published on his Wordpress site.

More and more journals are going open source or digitising. This is marvellous because it’s a real pain in the ass to go to the library, and your friends will distract you if they show up there too. But I will check your sources when I mark your work. I will without fail check any source I am not already academically familiar with, and if it smells like shit, I will feed back that the source was not compelling enough to support your argument. This is not “academik boolying“, this is my actual job. Not all sources are equally good. Quite a lot of shit gets vanity published, and a thing you need to know is which journals are the vanity journals in your field, and avoid ever relying on them. (Also don‘t submit your work to them for publication, it makes you look like a spastic who couldn‘t get published anywhere else).

You should refer to specific parts of the sources that support your argument. Don’t just throw a footnote in or say “As Chandler argues, blah blah blah”. Because then I will go and read Chandler like a Pharisee to see if they supoort your argument, and if they don’t I will be pissed at your laziness and your attempt to smokescreen me with a source that doesn’t support your argument, and I will take my feelings out on your grade. In fact I am required to ding you for that shit.

Once you have written all this shit up, you have to write a conclusion about whether or not the stuff you just wrote supports your thesis. If it doesn’t you better have a damn good reason why and be able to analyse why not.

The last thing you write is your introduction, because that tells me what you are you going to tell me in the rest of the paper, so it’s easiest to write this last because by then, you know what’s actually in the paper.

So, in recap, the first thing you need in your corona epic is a thesis. I think from all I have read of your train of thought, the thesis you are trying to prove is that coof is a neurotrophic virus. So focus on that and sources that prove that, and the individual strands of argument that will support that. Don’t fire hose links and tweets (you have to be ultra careful using fucking tweets as a source, okay?) without explaining how they supoort your thesis. Don’t get sidetracked.

You are familiar with popular science books. Try and aim for that informational but readily digestible tone in your writing.

Good luck with reworking your document. I’m interested to see the finished product.
 
Bravo for the post on technical writing, @Fareal! You pretty much nailed it, but I want to add a few things:

This.... is like teaching Chinese postgrads, and whoever handles induction for freshmen at your college should be assblasted for failing to insist on a mandatory course on citations and academic writing.
@Drain Todger has never gone to college, and has at best a high-school education (depending on whether he actually learned anything useful from his uneducated cultist parents when they were half-assedly homeschooling him).

todger.png
(https://archive.li/08Uv2#selection-2411.0-2411.19)

More and more journals are going open source or digitising. This is marvellous because it’s a real pain in the ass to go to the library, and your friends will distract you if they show up there too.
Here's a pretty useful resource for everyone that doesn't have university access to journal subscriptions for research articles (i.e. present for you, @Drain Todger!). Works pretty well for many articles that are otherwise paywalled, but of course some newer papers might not be immediately available if they haven't ripped them yet:

I think I posted this one too earlier, but I'll post it again. Pretty much everyone I knew at university used this, because fuck spending $200+ on a textbook.
 
Bravo for the post on technical writing, @Fareal! You pretty much nailed it, but I want to add a few things:


@Drain Todger has never gone to college, and has at best a high-school education (depending on whether he actually learned anything useful from his uneducated cultist parents when they were half-assedly homeschooling him).

View attachment 1222900
(https://archive.li/08Uv2#selection-2411.0-2411.19)


Here's a pretty useful resource for everyone that doesn't have university access to journal subscriptions for research articles (i.e. present for you, @Drain Todger!). Works pretty well for many articles that are otherwise paywalled, but of course some newer papers might not be immediately available if they haven't ripped them yet:

I think I posted this one too earlier, but I'll post it again. Pretty much everyone I knew at university used this, because fuck spending $200+ on a textbook.
There's this as well
 
How to write a paper 101
If we're actually talking about Academia, most would stop reading David Clop's shit after he failed to add brackets to his autistic equations. This is something incredibly simple and basic, there's no room for error when it comes to this type of shit. In fact, I will actually frown at anyone in university, teacher or student, for using the "÷" symbol. I've ridiculed engineering teachers for missing brackets in their lecture slides. All of them get the point and apologise for fucking up something so basic, David Clop blames it on calc.exe. I still have no idea how one copies an entire formula from the windows calculator.

Writing the actual paper will differ from person to person. I personally always start with the Introduction. I lay out the contents, this allows me to stay on point, instead of going off autistic tangents about unrelated shit. I never write the introduction last and personally do not recommend doing so.

Besides David Clop's inability to comprehend year one statistics, he also fails big time at what the field of statistics is about. This is illustrated by his links to fucking tweets. I honestly still feel dumb for not catching it right at the beginning, being 6am doesn't help my brain's lack of oxygen. I initially thought the "d^2" term in that anti-Tesla guy's tweet would be a predictor of some sort, I was overthinking it. Turns out it's merely a function that's force fitted onto a curve, which of course will result in high R-sq. It's unforgivable for people who know a bit about mathematics (studied Calculus I and II) to miss this, let alone PhDs that work in supposedly quantitative finance and biostatistics.

Take a look at Melody Goodman, the biostatistician that fit a curve to dots, called it regression analysis, and got puzzled by the high R-sq:
https://publichealth.nyu.edu/faculty/melody-goodman
https://archive.is/wip/3jCab

Here's her qualifications:
BS, Economics and Applied Mathematics & Statistics, State University of New York at Stony Brook, Stony Brook, NY
MS, Biostatistics, Harvard University, Cambridge, MA
PhD, Biostatistics (Minors: Social Determinants of Health Disparities and Theoretical Statistics), Harvard University, Cambridge, MA
And her "expertise":
Biostatistics
Community Health
Community-based Participatory Research
Dissemination and Implementation of Evidence-based Programs
Health Disparities
Health Equity
Minorities
Minority Health
Quantitative Research
One of her reputable studies: https://www.sciencedirect.com/science/article/abs/pii/S0277953618306580?via=ihub
How neighborhoods matter in fatal interactions between police and men of color
Highlights
•Minority threat and defense of inequality theories inform FIPs for males of color.
•Income inequality heightens the chances of a police homicide for Hispanic males.
•Lowered racial segregation reduces the odds of fatal injury for Black males.
•Racial segregation increased the odds of a police homicide for Hispanic males.
•Percentage of Hispanic officers raises risks of fatal injury for Hispanic males.

This article addresses the concern that death by legal intervention is a health outcome disproportionately experienced by boys and men of color, and predicated on the quality of the locations in which encounters with law enforcement occur. Using a more comprehensive cross-verified sample of police homicides from online databases and a nationally representative sample of law enforcement agencies, this study examines whether neighborhood social disorganization, minority threat, and defense of inequality theories help explain the odds that males of color will have a fatal interaction with police (FIP). There are several noteworthy results. First, in support of the defense of inequality thesis, we found that income inequality within the area in which a FIP occurred is related to increased relative odds of fatal injury for males of color and Hispanic males. Second, consistent with the minority threat thesis, we found low levels of racial segregation dramatically reduced the odds of a FIP for Black males while higher levels of segregation increased the odds for Hispanic males. Third, Hispanic males were over 2.6 times as likely as others to be killed by officers from agencies with relatively higher percentages of Hispanic officers. We conclude the study with a discussion of its implications for research and policy.

In general statistics, we work with P-values and what we call the "Null" and "Alternate" hypothesis.
Interpreting this stuff is very simple but there's a ton of misconceptions, displayed throughout the media and various shitty "journalism" pieces.

Null hypothesis is H0, Devil's advocate position, the "there's no difference" claim. Think of it as David Clop's Coronachan vaccine being tested and effectiveness analysed, compared to taking no vaccine or a placebo. H0 would be David Clop's vaccine being essentially the same as a placebo, ie it doesn't really work. H1, or the alternate hypothesis would be "there is a difference", ie it does work.

The null hypothesis can be rejected, or not rejected. However, the alternate hypothesis is never accepted as factual. There's always a chance which one fails to reject an H0 that's untrue, or rejects a true H0, called Type I and Type II errors. H0 is always assumed to be true, similar to how the law works, a person's innocence is assumed.

P-value is the probability of acquiring results that are as extreme as the sample being analysed. It's usually set at 0.05 when teaching. A P-value smaller than 0.05 means zero difference, ie a medicine has no effect. If the P-value is 0.04, this means the treatment has no effect, and 4% studies will yield the same mean difference, or more, compared to your study.

P-value isn't the probability of making a Type I or II error.
Type I: A true null hypothesis being rejected.
Type II: An untrue null hypothesis not being rejected.

Chance of making an error based on p-value is entirely different. P-value of 0.05 comes with a 23-50%+ chance of making an error.

Some in the field of statistics like to call this semantics and ignore all the misconceptions, some even use them. Lots of people simply misuse studies that feed into their confirmation bias and back it all up with academic drivel as an attempt to sound convincing. My typical response to this behaviour is "this is the difference between scientists, statisticians, and people who know which button to click on a program".

I'm guilty of such misconceptions as well. This is however entirely my fault. I skip all lecture classes and study at home, sometimes "traps for young players" aren't emphasised on in text books. However as one learns and has more practical experience, all these errors will be realised and corrected. Hopefully this is the case for David Clop.

All this, David Clop would actually know if he listened in class, or spent time studying while skipping classes (guilty here), or if he actually spent lots of time and money to get a proper degree that's worth more than the piece of paper it's written on.

This is exactly why everyone should be extremely cautious when encountering statistics that's masked in academic word salads. Whether it's the alt-right types talking about race realism and IQ, Destiny types scatterbombing studies, or MSM trying to make sense of numbers they aren't qualified to look at. Conclusion is simple, none of these numbers are generated by a spreadsheet, because the original method to supposedly prove this was fundamentally flawed. As for the other shit I won't even try to pretend that I'm qualified in, I've seen people doing a great job at countering those.
 
Have to agree on the intro: I love using outlines to plot out papers, and what I always do is I write a thesis statement at the very least (your entire paper's point), which I then attempt to back up with sources first. If I can't pull it off, then that just means I need a new thesis, since I can't really fucking prove or back up said statement (HINT HINT DAVID). When I know I at least have some data and sources that aren't complete shit, then I flesh out the introduction from said thesis, and THEN go further from there.

Like shit, this is college 101, meaning this idiot never went or is busy failing it on Norman Osbourne's money. Probably should just lick his doorknobs tbh.
 
As a matter of fact, no, I do not engage in stolen valor. I am open and transparent about my employment, and I would thank you not to accuse me of things I don't do.

True & Honest Sailor

By the by, not every source is created equal. In my geology undergrad we were exposed to creationist journals that, while having the veneer of scientific legitimacy, were just outfits to proselytize their given sect of Christianity instead of furthering the science. While I have no qualms with people having different beliefs and opinions, I do have a problem with people misrepresenting the truth to fit their predetermined outcomes.
These creationist outfits would not only misrepresent how the radiological dating of rocks works, they would then proclaim that the current methods are egregiously inaccurate and their their "alternative" method gave them a date for the Earth's age that just so happens to line up with what Biblical scholars interpreted from the Old Testament. Of course they either won't share their techniques or their results cannot be reproduced from the procedures outlined in their paper.

This method of manipulation, obfuscation, and omission of data is how you get Flat Earthers. They not only buy into bogus "science", they then buy into the narrative that they have the truth and are being suppressed when in reality they couldn't be further from the truth.

On a similar note, confirmation bias is very real in the sciences. The old hypothesis of geosyncline was accepted as the proper model for continental movement until the US Navy released bathymetric maps of the world's oceans. Those maps revealed structures that gave Alfred Wegener's continental drift hypothesis a functional mechanism that was found to have almost irrefutable evidence in the form of seismic tomographic images that very clearly show evidence of subduction. For reference, continental drift/plate tectonics has only been accepted as geology's prevailing theory for ~40 years. My father was taught geosyncline in his intro to geology courses with his fossil of a professor calling plate tectonics "New Age hippie shit". Scientists can and will fall into the trap of "it's always been like this, there's no way that hypothesis A is wrong. Hypothesis B is for schmucks!"

TL ; DR - Don't trust every source you see. If results cannot be replicated by people just reading the paper then the methods used are intrinsically flawed, data has been omitted or manipulated, or the author(s) suck at writing. Additionally, just because a paper's author may be an expert in their field doesn't mean that they're immune to confirmation bias. This is why peer-review is the gold standard in the sciences.
 
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All this, David Clop would actually know if he listened in class, or spent time studying while skipping classes (guilty here),
Like shit, this is college 101, meaning this idiot never went or is busy failing it on Norman Osbourne's money. Probably should just lick his doorknobs tbh.
😑
@Drain Todger has never gone to college, and has at best a high-school education (depending on whether he actually learned anything useful from his uneducated cultist parents when they were half-assedly homeschooling him).

You guys have some interesting takes on paper introductions though! I've always just done it the 'introductions last' way myself and I've found that to work for me, but I might try mixing it up a bit on my next paper.

On Scholarly Articles <and accuracy of sources>
Also seconded! And actually you reminded me that RetractionWatch is a thing, so I went and had a look to see if they had anything to say about the latest COVID-19 papers that have been coming out. Behold:
(https://archive.li/xtVst)
(https://archive.li/KXknM)
(https://archive.li/8ct9Q)

So to add to @Mr. Skeltal's point, don't blindly trust something just because it has ostensibly made it through peer review, either. Papers get retracted for faking peer review/plagiarism/falsifying data/manipulating images/failing standards of responsible research conduct/etc all the goddamn time.
 
You guys have some interesting takes on paper introductions though! I've always just done it the 'introductions last' way myself and I've found that to work for me, but I might try mixing it up a bit on my next paper.
The ideal, in a scientific paper, is that your introduction is the hypothesis you wish to test, which means there should be a chance that your conclusion contradicts it. Of course, papers that don't result in the expected outcomes are generally less favoured when it comes to the handing out of further grants, so there's a tendency to fudge the hypothesis to match the outcomes and then tack on a "further study is needed" (gibmedatas) suffix so that the lab can continue to pay its bills.

The confounding variable is whether you write a paper based on studies already undertaken, or write a paper on studies currently under investigation. The former allows you to write the introduction in the knowledge that it will match the conclusion. The latter is more fraught.
 
The ideal, in a scientific paper, is that your introduction is the hypothesis you wish to test, which means there should be a chance that your conclusion contradicts it. Of course, papers that don't result in the expected outcomes are generally less favoured when it comes to the handing out of further grants, so there's a tendency to fudge the hypothesis to match the outcomes and then tack on a "further study is needed" (gibmedatas) suffix so that the lab can continue to pay its bills.

The confounding variable is whether you write a paper based on studies already undertaken, or write a paper on studies currently under investigation. The former allows you to write the introduction in the knowledge that it will match the conclusion. The latter is more fraught.
It's the main reason why academia is so fucking toxic these days, it's not the miniscule SJW faggotry it's adopting China's "Save Face" strat.

Science is slowly starting to deny it can ever be wrong, and it's fucking bullshit. Also ironic that something religions tried to yeet is now trying to be a religion itself.
 
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