Bayesian Vs. Frequentist Statistics

In this video Emily explains the difference between a Bayesian approach and a frequentist approach to analyzing statistics. A Bayesian analysis looks at prior probabilities combined with data to determine the probability that the hypothesis is true. A frequentist analysis compares the hypothesis to the null-hypothesis, a yes/no approach, to determine if the data could support the null-hypothesis. It then ranks the data with a P-value, but it actually says nothing about the hypothesis being true.

Losing Faith In Medical Research

In February of 2023 Dr. Kendrick spoke at BSI’s event in Phoenix, AZ. Malcom’s presentation recaps the history of the diet-heart hypothesis, the supposed link between cholesterol and cardiovascular death, and how drug companies have fooled doctors into prescribing medications that are harming patients rather than helping them.

P-Values Explained

Simply put, a p-value is a measure of the likelihood that the results of a study are due to the hypothesis, and not simply a result of chance. It compares the “null hypothesis,” the idea that the thing being studied has no effect, vs the “alternative hypothesis,” the thing being tested. So if the p-value is low, the data is thought to be significant. However, the p-value does not validate the effectiveness of the thing being studied, it simply claims to shows that the results were not due to chance.

Frighteningly, scientists, researchers, and medical professionals misinterpret the meaning of p-values but place extreme faith in them.

William Briggs – Ranch Jun 2023

William Briggs builds upon Greg Glassman’s Castro Ranch talk introducing The Broken Science Initiative. Briggs emphasizes that his critique is not aimed at all types of science, but rather at the growing prevalence of broken and bad science. Briggs highlights two especially impactful examples of broken science, namely the COVID “panic” and climate change. Using these examples, Briggs demonstrates how reliance on flawed models and blind trust in “the science” has lead to severe political and social ramifications for everyone.