The article clarifies the meanings of α and β in clinical research. α is the chance of wrongly rejecting a true hypothesis, while β is the chance of wrongly accepting a false hypothesis. These probabilities are based on whether the hypothesis is true or false in the population, not just in the sample data. P values show how extreme the data is compared to the null hypothesis. Power is like the sensitivity of a test, not the specificity. It's important to understand these concepts to interpret research results accurately.