Apparent 74% increase in death in first 381 days
More analysis of the Medicare data dump from Steve Kirsch
In Steve Kirsch’s Substack here, you find the Medicare death data of over 114,000 people.
Special Note: Subsequent sensitivity analysis, such as is presented here, reveals danger that is “present” but less “clear.”
I formed a 99% exact binomial confidence interval around the proportion of the total deaths that occurred within 381 days or less of getting jabbed and compared it to the 99% exact binomial confidence interval around the proportion who died from Day 382 to Day 763 after the jab.
If 99% confidence intervals do not overlap then, take my word for it, it is a big deal. Here are the notes showing how it appears to be the case that early deaths are 74% more likely than deaths after Day 381 post-jab:
[click image to enlarge]
The formula for cell M4 (lower bound on proportion of deaths prior to Day 382) shows up at top in case you want to recreate my findings. The Excel code for the upper bound of the interval is given at top right.
The ratio of people dying in the first 381 days, divided by the number of people who died from Day 382 to Day 763, was 1.74. Half of everyone in the data table died by Day 299 post-jab.
Caveat: All data is on deaths though, and the survivors are missing from this table. Even still, being 74% more likely to die in the first 381 days was statistically significant. One can expect a few more deaths to be found early, but not 74% more.
Isn’t it great? What happens when you set the data free so that everyone can analyze the data?
It’s a mystery to me why the CDC is keeping the Medicare data under wraps.
I just released a good portion of it, and nobody has complained to me about a privacy violation