Understanding False Postive Psychology

The table_1.ipynb Jupyter notebook attempts to reproduce Table 1 in False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant by Joseph P. Simmons, Leif D. Nelson, and Uri Simonsohn.. The paper shows that simple decisions made by an experimenter after looking at the data can lead to incorrect statistics and a high false positive rate. This is often called p-hacking, though is often not done with nefarious intentions. The paper reinforces how important it is to determine your experiment and analysis design up front, before data analysis commences.