How is marginal probability calculated?

Marginal probability is calculated by determining the likelihood of a specific event occurring within a sample space. This is done by taking the number of times the event occurs and dividing it by the total number of occurrences or outcomes in the entire sample space. This method provides a straightforward approach to understanding how often a particular event is likely to happen relative to the overall set of data.

To visualize this, consider a scenario where you are looking at a dataset that includes various outcomes of a healthcare study. If you want to find the marginal probability of a patient recovering from a treatment, you would count all the patients who recovered (the event occurrences) and divide that by the total number of patients in the study (the total occurrences). This calculation gives you the proportion of recovery, which is the marginal probability for that event. This understanding is fundamental in statistics as it helps in making inferences based on the data collected.

Other approaches suggested, like dividing a subset by the total and multiplying by 100, relate more to obtaining percentages rather than directly calculating marginal probabilities. Similarly, subtracting occurrences from 100 or reversing the numerator and denominator do not align with the standard definition and calculation method associated with marginal probability.