Source: Corey Seamster | Image: Screenshot of Excel of 3DR – Sample Marketing Data

Based on a hypothetical scenario, if 3DR decided to implement Bayesian Paradigms in their marketing efforts, they would have visibility into information that perhaps they would not normally be able to gain insight on. Given the 3DR Marketing Data by Company Responsibility, for instance, 3DR can identify the probability that the winner is either a male or is in the Sales/Marketing category by using the union probability formula (Black, 2020).

Union Probability Formula (Black, 2020):

As outlined above, there is a 74.3% chance that the winner is either a male or is in the Sales/Marketing category.

Moving on, what if 3DR wanted to know what is the probability that the winner is a male from the Engineering/Technical Lead category? In this particular case, 3DR can use the joint probability formula to get their answer.

Joint Probability Formula (Black, 2020):

As outlined above, there is a 4.7% chance that the winner is a female from the Engineering/Technical Lead category.

Lastly, what if 3DR wanted to know what is the probability that the winner is from the Project Manager category and it is known that it is a male? In this particular case, 3DR can use the Conditional probability formula to get their answer.

Conditional Probability Formula (Black, 2020):

As outlined above, there is a 46.3% chance that the winner is from the Project Manager category knowing that the attendee is a male.

All in all, Bayesian statistics can be applied to a variety of different business case scenarios to gain useful information on populations. As outlined in the 3DR analysis above, Bayesian statistical approaches could very well serve 3DR in its effort to identify insights on its attendees and target customers.