In this episode, Professor Konstantin Slavin reads aloud an article by Garston Liang, Quentin F. Gronau, and Alexander Thorpe which discusses the p-value, a fundamental concept in statistical analysis, and clarify what it can and cannot tell you about your data. Key points include:

• What a p-value tells you: The probability that a null hypothesis generated the observed data.
• What a p-value cannot tell you: The effect size, the quality of alternative hypotheses, the presence of an effect, details of the sampling plan, or data pre-processing steps.

The hosts explore the limitations of p-values, emphasizing the importance of understanding their context and proper usage in scientific research. Tune in to gain a deeper insight into the role of p-values in hypothesis testing and avoid common misconceptions.

Resources:

1. Biostatistics articles on the INS website
2. What a P-value can and cannot tell you article