Statistically unheard of. When will the mainstream media finally address this? This can’t be ignored. (h/t @EthicalSkeptic and Dr. Simon Goddek @goddeketal )

19 sigma in statistics is an extremely rare event, as it implies that the event has a probability of occurrence of only about 0.000000000000233 or 0.000000233%. In practical terms, this means that if a process is 19 sigma, it should essentially be perfect, with no errors or anomalies.

A 19 sigma spike in cardiac problems would be an extraordinarily unusual increase in heart-related issues. Given the rarity of a 19 sigma event, this would mean that the increase in cardiac problems is practically impossible under normal circumstances, suggesting that there may be some extraordinary or unprecedented factors at play. However, it’s important to note that in real-world scenarios, it’s unlikely for any process to be 19 sigma, let alone a complex and multifactorial issue like cardiac problems.

The CDC’s WONDER (Wide-ranging ONline Data for Epidemiologic Research) website provides provisional death counts for COVID-19. These data are presented in a tabular format, with various columns providing different pieces of information such as the week of death, age group of the deceased, sex, and race.

When interpreting these data, you might want to consider the following:

1. Trends over time: Look at how the number of deaths changes over the weeks. This can give you an idea of how the COVID-19 situation is evolving.
2. Demographic differences: Compare the number of deaths across different age groups, sexes, and races. This can help identify which groups are being affected the most.
3. Provisional vs. final data: Remember that this is provisional data, meaning it’s subject to change as more information becomes available. Final data may provide a more complete and accurate picture.
4. Contextual factors: Consider other factors that might be influencing the data, such as changes in testing rates, public health interventions, or social behaviors.

To interpret the data effectively, you might want to use data analysis or statistical software to perform more detailed analyses. This could involve calculating percent changes, creating visualizations, or applying statistical tests.

In Norway, there has been an explosion in use of heart medicine in young (15-44) after Covid injections began, reports Jarle Aarstad in Norway. @jarleaarstad or jarle.substack.com (link to article below.)

Explosive increase in the use of heart medicine among young, 15-44 yrs., in Norway after covid vaccine rollout.

In the following shocking and enlightening interview on thehighwire.com, Dr. Naomi Wolf, a feminist and journalist, reveals details from Pfizer’s own research documents including primary sources not opinions, especially on reproduction problems, the so-called soon to be infamous “Pfizer Papers”. This is 49 minutes and very worthwhile your time.

If this video is removed or not working, please let me know.