My response:Blackvegetable » 02 Apr 2025, 1:39 pm » wrote: ↑
02 Apr 2025, 1:39 pm
so your example is NOT one of Sampling error..
therefore it cannot be an example of Survivorship bias.
QED.
I continued to demoralize him here:No, Veghead, that’s not how logic—or survivorship bias—works. Sampling error is one way survivorship bias can occur, not the only way. Survivorship bias is about drawing conclusions based only on those who made it through a process, while ignoring those who didn’t. That can happen in analysis, reporting, or interpretation—not just sampling.
So yes, my example is survivorship bias because it critiques how focusing only on net job gains ignores losses, labor force exits, and job quality. That’s not a data collection flaw—it’s a cognitive blind spot in how the results are interpreted and presented. But sure, slap “QED” on it and pretend you just won a debate you never actually participated in.
QED
And he continued to demoralize himself here:What is "survivorship bias?" . Your words only, without my help. And **** your "sampling error" ****. Put some substance to it. There are a million types of sampling errors that do not include survivorship bias. Moron.
What is "net jobs?" Your words only, without my help.
Oh my God. You are so **** hopeless. Survivorship bias is a sampling error? That’s like saying a heart attack is just a little chest discomfort. Sure, it involves flawed sampling, but reducing it to that completely misses the point. The real issue is how it distorts interpretation by focusing only on the “survivors” and ignoring the losses, failures, or those filtered out of the dataset. It absolutely shapes perception—especially in economics, finance, and public policy, because people draw conclusions from what’s visible, not from what’s missing. That’s the entire danger of the bias. Idiot. But hey, keep pretending it’s just a stats footnote if that helps you sleep through your own argument.Blackvegetable » 02 Apr 2025, 12:09 pm » wrote: ↑
02 Apr 2025, 12:09 pm
Sirvivorship bias is a SAMPLING error.
Sampling is a statistical exercize...
It isn't about "perception"
This isn't for innumerate Level 0.16s..
My response:Blackvegetable » 02 Apr 2025, 1:53 pm » wrote: ↑
02 Apr 2025, 1:53 pm
I've already defined the levels.
You lose at every one.
To which you replied with this genius response:Your definition was "It's a sampling error."![]()
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Yeah, no ****. So are 300 other types of biases
Then I handed your *** here:Blackvegetable » 02 Apr 2025, 2:04 pm » wrote: ↑
02 Apr 2025, 2:04 pm
No....that's a lie.
List them
Every one...and make sure they are all sampling errors.
I show that you said it was a sampling error, and you take off a month. Deal?
300 was obviously a hyperbole you **** idiot. I am not going to list all of them. This is enough to embarrass you:
1. Selection Bias: Occurs when the sample collected is not representative of the population intended to be analyzed, leading to skewed results.
Example: Studying only people who responded to an online survey about internet use. You’re automatically excluding non-users, skewing your conclusions.
2. Undercoverage Bias: Occurs when some members of the population are inadequately represented in the sample.Example: A telephone survey using landlines will miss younger people who mostly use cell phones, underrepresenting their opinions.
3. Exclusion Bias: Happens when certain groups are deliberately or accidentally left out of the sample.Example: A medical trial that excludes elderly participants, even though the treatment is intended for all adults.
4. Publication Bias: This happens when studies with significant or positive findings are more likely to be published, and thus more likely to be included in reviews or meta-analyses.Example: A new drug appears highly effective in the literature, but dozens of unpublished trials with null results were never seen.
You lose.Vegas » 26 May 2025, 3:42 pm » wrote: ↑ @Blackvegetable @Cannonpointer
This is where it started: digest.php?u=1050&start=1040
My response:
I continued to demoralize him here:
And he continued to demoralize himself here:
Oh my God. You are so **** hopeless. Survivorship bias is a sampling error? That’s like saying a heart attack is just a little chest discomfort. Sure, it involves flawed sampling, but reducing it to that completely misses the point. The real issue is how it distorts interpretation by focusing only on the “survivors” and ignoring the losses, failures, or those filtered out of the dataset. It absolutely shapes perception—especially in economics, finance, and public policy, because people draw conclusions from what’s visible, not from what’s missing. That’s the entire danger of the bias. Idiot. But hey, keep pretending it’s just a stats footnote if that helps you sleep through your own argument.
Vegas » 26 May 2025, 4:20 pm » wrote: ↑ @Blackvegetable
Oh ****. I just found another one. LOL
My response:
To which you replied with this genius response:
Then I handed your *** here:
That copy paste is from the beevee account - and the banning was withdrawn in thirty days.
Done.Vegas » 26 May 2025, 4:43 pm » wrote: ↑![]()
This is what happens to narcissists. You always end up losing. Your memory is ****.
@Cannonpointer Please proceed to put "Beevee' Owner" on my profile at your earliest convenience.
What "banning"?Cannonpointer » 26 May 2025, 6:33 pm » wrote: ↑ That copy paste is from the beevee account - and the banning was withdrawn in thirty days.
You pathetic hack.
What "screen shot"?