If the vaccines are safe, the number of deaths reported after dose 1 vs. dose 3 should be statistically similar. They were not the same. There was a 13-fold difference in death reports.
Why say nothing? We have to warn people even if they hate us. I live set apart from the world don't care if people think I am crazy. I please God not man.
My pediatrician said he wasn’t comfortable give my teen that shot. He said children are dying & 1 death is too many. Some of my friends were at different drs. Those drs harassed them to inject their daughters. My friend had to argue that she wasn’t getting it. Drs are just as responsible.
But why did you just pump out (July 6th) an offshore scam broker advertisement??
It states, "50% returns!" That's illegal.
And no name - wonder why?
And you state that you use them?? Not likely. (And whatever happened to your hedge fund...) I post this here because you've locked out the comments on that most recent email.
None of the safety trials for Gardasil used a 'saline' placebo. Instead, the placebo contained at a minimum Polysorbate 80, sodium borate (Borax), genetically modified yeast, and L-histidine.
In other trials, Merck used AAHS, Gardasil’s aluminum-containing adjuvant, as the primary control.
Claude.ai (Sonnet 5 High model) gives a p value of 0.0018 (about 1 in 500 odds the difference is due to chance alone. Claude query and response below:
## Original query (restated)
*Given two counts from a random (Poisson) process — 13 events in one time period and 1 event in a second time period — what is the proper way to measure the statistical significance of the difference between them?*
## Setup
We're comparing two counts, *count_1 = 13* and *count_2 = 1*, assumed to come from Poisson processes. We want to test whether the difference between them is more than random noise would explain.
The standard, exact method for this is the **conditional binomial test** (sometimes called the **C-test**).
### Step 1: Condition on the total
Let *total = count_1 + count_2 = 14*.
Under the null hypothesis that both periods share the *same* underlying event rate (and the same exposure time), each of these 14 events is, independently, equally likely to have occurred in period 1 or period 2. That "equally likely" number is our binomial parameter.
### Step 2: Define the binomial parameter — *odds_of_success*
Call this parameter *odds_of_success* — the probability that any single one of the 14 events falls into period 1, under the null hypothesis.
- If the two periods have **equal exposure time**: *odds_of_success = 0.5* (a fair-coin assumption).
- If the periods have **different exposure times** *t_1* and *t_2*: *odds_of_success = t_1 / (t_1 + t_2)*.
### Step 3: Compute the p_value
We then ask: under a Binomial(*total*, *odds_of_success*) distribution, what is the probability of observing a split at least as extreme as *count_1 = 13* vs. *count_2 = 1*, in either direction? That probability is the *p_value*.
Recomputing with the equal-exposure assumption (*odds_of_success = 0.5*):
$$p\_value \approx 0.0018$$
## Interpretation
| Name | Role | Value |
|---|---|---|
| *odds_of_success* | probability a given event lands in period 1, under the null hypothesis | *0.5* (assuming equal exposure time) |
| *p_value* | probability of a split at least this extreme, assuming *odds_of_success* is correct | *≈ 0.0018* |
Since *p_value ≈ 0.0018* is far below common thresholds like *0.05*, this is strong evidence that the two periods do **not** share the same event rate — the difference between 13 and 1 is unlikely to be due to chance alone.
**One caveat worth flagging again:** this all assumes the two time periods had equal length. If they didn't, *odds_of_success* should be set to *t_1 / (t_1 + t_2)* instead of *0.5*, and the *p_value* would change accordingly. Let me know the two exposure times if you'd like the corrected version.
Maybe at some point the alternative health community will look at root causes, in this case all the false advertising and propaganda on "the joy of sex", how important sex is for your health, how not having sexual outlets can make people neurotic. I have no doubt that sex is a powerful social economic thing for many people, but it is also highly compromising with complex consequences often not good. People, even spouses pushing others to have sex even against their wills are doing wrong.
As Henry Thoreau said: “Chastity is the flowering of man; and what are called Genius, Heroism, Holiness, and the like, are but various fruits which succeed it”. The perverse invention of the word "incel", ie "involuntary celibate" is particularly disgusting. Many celibates could find others to couple up with, in fact no one is so unattractive to not have a mate as long history has proven. What is gained frequently in sex except procreation? Themes are expressed in Shakespeare's "sonnet 129" and others like sonnet 151 on the problem passions.
Alternative health professionals should fully educate people, especially the young on the consequences of sex and the explosion of sex-related products, problems, promotions and consequences. We have "positive" books such as "The Joy of Sex" but not alternative ones such as "The Miserable Consequences of Sex". It is my personal opinion that oral sex is unhealthy even with modern hygiene. Same thing with viagra. When performed on the man it is overly stimulating without a corresponding effect in the woman and in some it leads to cognitive degradation. How is the guy going to recover from extremely stressful sex? All the natural, health boosting juices and substances in the world are unlikely to return the body to balance.
I'm laughing once again ! All the so called vaccines were dangerous concoction of chemicals untested, unvetted , zero safety or years of data and research from outside testing companies to even talk about approval to inject into human beings ! And the masses lined up with arms out and ready to inject the poison into their bodies - just proves how fucking stupid lazy and government dependent half the country have become people dying all the time as result of the jabs - hello communism!!
The burden of proof of safety is with the manufacturers, not Steve. So long as the safety trials lack a proper placebo, the vaccine must be considered unsafe until proven otherwise.
Know, too, that the pharma and mainstream (captured) medical industries do two things at once with regards to VAERS: They dismiss it as unreliable and unscientific while at the same time absolutely refusing to create an alternative system. They also refuse to do any follow-up investigation with the cases that are logged in order to prove that the cases therein are "false or misleading." This is consistent with not only knowing what the results of such investigations would reveal but also demonstrating that VAERS is actually accurate enough to prove beyond any reasonable doubt that it under-counts the true risk. VAERS is simultaneously the most damning body of evidence against vaccines (and many other drugs) and the perfect strawman they can use to sway the dishonest brokers and the gullible.
Of course. Any industry that has 30% of every product introduced, pulled from the market likely has a much greater percentage that should also be pulled from the market, except maybe antibiotics or steroids.
Let's start with the premise that ALL vaccines are never safe and effective. No HHS retardism required. There is no proof to the contrary. Is there anyone with a reasonable thought process that can make a case for vaccines when they contain toxic and poisonous ingredients that the body has absolutely no use for?
The point is that people in a country this size are dying all the time, and people are getting vaccinated all the time, so there is going to be some coincidence in time between vaccinations and deaths. The key is to find data that shows it was not coincidence. Are the deaths randomly distributed, or non-randomly clustered after vaccinations?
13 deaths after dose 1 and only 1 death after dose 3 is not a random distribution. The 1 death after dose 3 could just be random coincidence, so you can't say it shouldn't happen if the vaccine were safe.
Why say nothing? We have to warn people even if they hate us. I live set apart from the world don't care if people think I am crazy. I please God not man.
My pediatrician said he wasn’t comfortable give my teen that shot. He said children are dying & 1 death is too many. Some of my friends were at different drs. Those drs harassed them to inject their daughters. My friend had to argue that she wasn’t getting it. Drs are just as responsible.
Great info on Gardasil, Steve.
But why did you just pump out (July 6th) an offshore scam broker advertisement??
It states, "50% returns!" That's illegal.
And no name - wonder why?
And you state that you use them?? Not likely. (And whatever happened to your hedge fund...) I post this here because you've locked out the comments on that most recent email.
Have you become a Scammer?
It is still injuring young girls and boys. Let the adults take the chance. But oh. They don't want to take a risk. Leave the kids alone.
None of the safety trials for Gardasil used a 'saline' placebo. Instead, the placebo contained at a minimum Polysorbate 80, sodium borate (Borax), genetically modified yeast, and L-histidine.
In other trials, Merck used AAHS, Gardasil’s aluminum-containing adjuvant, as the primary control.
It's turtles all the way down!
Claude.ai (Sonnet 5 High model) gives a p value of 0.0018 (about 1 in 500 odds the difference is due to chance alone. Claude query and response below:
## Original query (restated)
*Given two counts from a random (Poisson) process — 13 events in one time period and 1 event in a second time period — what is the proper way to measure the statistical significance of the difference between them?*
## Setup
We're comparing two counts, *count_1 = 13* and *count_2 = 1*, assumed to come from Poisson processes. We want to test whether the difference between them is more than random noise would explain.
The standard, exact method for this is the **conditional binomial test** (sometimes called the **C-test**).
### Step 1: Condition on the total
Let *total = count_1 + count_2 = 14*.
Under the null hypothesis that both periods share the *same* underlying event rate (and the same exposure time), each of these 14 events is, independently, equally likely to have occurred in period 1 or period 2. That "equally likely" number is our binomial parameter.
### Step 2: Define the binomial parameter — *odds_of_success*
Call this parameter *odds_of_success* — the probability that any single one of the 14 events falls into period 1, under the null hypothesis.
- If the two periods have **equal exposure time**: *odds_of_success = 0.5* (a fair-coin assumption).
- If the periods have **different exposure times** *t_1* and *t_2*: *odds_of_success = t_1 / (t_1 + t_2)*.
### Step 3: Compute the p_value
We then ask: under a Binomial(*total*, *odds_of_success*) distribution, what is the probability of observing a split at least as extreme as *count_1 = 13* vs. *count_2 = 1*, in either direction? That probability is the *p_value*.
Recomputing with the equal-exposure assumption (*odds_of_success = 0.5*):
$$p\_value \approx 0.0018$$
## Interpretation
| Name | Role | Value |
|---|---|---|
| *odds_of_success* | probability a given event lands in period 1, under the null hypothesis | *0.5* (assuming equal exposure time) |
| *p_value* | probability of a split at least this extreme, assuming *odds_of_success* is correct | *≈ 0.0018* |
Since *p_value ≈ 0.0018* is far below common thresholds like *0.05*, this is strong evidence that the two periods do **not** share the same event rate — the difference between 13 and 1 is unlikely to be due to chance alone.
**One caveat worth flagging again:** this all assumes the two time periods had equal length. If they didn't, *odds_of_success* should be set to *t_1 / (t_1 + t_2)* instead of *0.5*, and the *p_value* would change accordingly. Let me know the two exposure times if you'd like the corrected version.
https://gist.github.com/MathematicalSoftware/605280a699cc0a76c891fdb44d750369
Downloaded and viewable python code to compute the p-value (odds that difference is due to chance alone)
Python code from Claude.ai to compute on your computer with Python and add on packages NumPY, Scipy installed.:
#!/usr/bin/env python3
"""
compare_counts.py
Compare two Poisson-process event counts using the conditional
binomial test (C-test) and report the p_value.
Usage:
python3 compare_counts.py [count_1] [count_2]
count_1, count_2 Two non-negative integer event counts.
Defaults to 13 and 1 if not provided.
Assumes both counts were observed over EQUAL exposure/time periods
(odds_of_success = 0.5). If your exposure times differ, edit
odds_of_success below.
Options:
-h, --h, -help, --help Show this help message and exit.
"""
import sys
from scipy.stats import binomtest
HELP_FLAGS = {"-h", "--h", "-help", "--help"}
def main():
args = sys.argv[1:]
if any(a in HELP_FLAGS for a in args):
print(__doc__)
sys.exit(0)
if len(args) == 0:
count_1, count_2 = 13, 1
elif len(args) == 2:
try:
count_1, count_2 = int(args[0]), int(args[1])
except ValueError:
print("Error: count_1 and count_2 must be integers.\n")
print(__doc__)
sys.exit(1)
else:
print("Error: expected 0 or 2 arguments.\n")
print(__doc__)
sys.exit(1)
if count_1 < 0 or count_2 < 0:
print("Error: counts must be non-negative.")
sys.exit(1)
total = count_1 + count_2
odds_of_success = 0.5 # assumes equal exposure time in both periods
if total == 0:
print("Both counts are zero; p_value is undefined.")
sys.exit(1)
result = binomtest(count_1, total, odds_of_success, alternative="two-sided")
print(f"count_1 = {count_1}")
print(f"count_2 = {count_2}")
print(f"total = {total}")
print(f"odds_of_success = {odds_of_success}")
print(f"p_value = {result.pvalue:.5f}")
if __name__ == "__main__":
main()
i see an error.
Maybe at some point the alternative health community will look at root causes, in this case all the false advertising and propaganda on "the joy of sex", how important sex is for your health, how not having sexual outlets can make people neurotic. I have no doubt that sex is a powerful social economic thing for many people, but it is also highly compromising with complex consequences often not good. People, even spouses pushing others to have sex even against their wills are doing wrong.
As Henry Thoreau said: “Chastity is the flowering of man; and what are called Genius, Heroism, Holiness, and the like, are but various fruits which succeed it”. The perverse invention of the word "incel", ie "involuntary celibate" is particularly disgusting. Many celibates could find others to couple up with, in fact no one is so unattractive to not have a mate as long history has proven. What is gained frequently in sex except procreation? Themes are expressed in Shakespeare's "sonnet 129" and others like sonnet 151 on the problem passions.
Alternative health professionals should fully educate people, especially the young on the consequences of sex and the explosion of sex-related products, problems, promotions and consequences. We have "positive" books such as "The Joy of Sex" but not alternative ones such as "The Miserable Consequences of Sex". It is my personal opinion that oral sex is unhealthy even with modern hygiene. Same thing with viagra. When performed on the man it is overly stimulating without a corresponding effect in the woman and in some it leads to cognitive degradation. How is the guy going to recover from extremely stressful sex? All the natural, health boosting juices and substances in the world are unlikely to return the body to balance.
I'm laughing once again ! All the so called vaccines were dangerous concoction of chemicals untested, unvetted , zero safety or years of data and research from outside testing companies to even talk about approval to inject into human beings ! And the masses lined up with arms out and ready to inject the poison into their bodies - just proves how fucking stupid lazy and government dependent half the country have become people dying all the time as result of the jabs - hello communism!!
Regardless of how noble the goal is, one (1) sample is not enough for any reliable statistical references.
True, but where is your counter data?
The burden of proof of safety is with the manufacturers, not Steve. So long as the safety trials lack a proper placebo, the vaccine must be considered unsafe until proven otherwise.
It will take a few minutes to find the details about the “placebo” in the trials for the HPV vaccines in this list : https://scientificprogress.substack.com/p/1-second-package-insert-challenge?r=3rhk2&utm_campaign=post&utm_medium=email
My twin daughters received it in 2006, at age 12 and one of them lost any ovary, because of a massive 8lb tumor!
Know, too, that the pharma and mainstream (captured) medical industries do two things at once with regards to VAERS: They dismiss it as unreliable and unscientific while at the same time absolutely refusing to create an alternative system. They also refuse to do any follow-up investigation with the cases that are logged in order to prove that the cases therein are "false or misleading." This is consistent with not only knowing what the results of such investigations would reveal but also demonstrating that VAERS is actually accurate enough to prove beyond any reasonable doubt that it under-counts the true risk. VAERS is simultaneously the most damning body of evidence against vaccines (and many other drugs) and the perfect strawman they can use to sway the dishonest brokers and the gullible.
Of course. Any industry that has 30% of every product introduced, pulled from the market likely has a much greater percentage that should also be pulled from the market, except maybe antibiotics or steroids.
Let's start with the premise that ALL vaccines are never safe and effective. No HHS retardism required. There is no proof to the contrary. Is there anyone with a reasonable thought process that can make a case for vaccines when they contain toxic and poisonous ingredients that the body has absolutely no use for?
The virus is not something that can be studied day 1, and be treated day 45 with significant success. IMO .THEY MUTATE !
Is that so?
The problem with your statement is that it's built on the false premise pathogenic viruses exist and cause disease.
To date, this has not been proven using the scientific method and logical inference.
If you have direct evidence, please share.
A safe vaccine would have no deaths.
Good point.
A safe vaccine would have NO toxic poisons in its contents and thusly it is impossible to make a safe and effective vaccine.
The point is that people in a country this size are dying all the time, and people are getting vaccinated all the time, so there is going to be some coincidence in time between vaccinations and deaths. The key is to find data that shows it was not coincidence. Are the deaths randomly distributed, or non-randomly clustered after vaccinations?
13 deaths after dose 1 and only 1 death after dose 3 is not a random distribution. The 1 death after dose 3 could just be random coincidence, so you can't say it shouldn't happen if the vaccine were safe.