Lilian Elohor Emukowhate Written by Lilian Elohor Emukowhate · 1 min read >

Now that I’m in business school, I’m attempting to connect what I’m learning to my everyday life. Whether it’s figures or just ideas.

When it comes to incorporating probability thinking into our daily lives, Bayes’ theorem provides a straightforward solution. For me I think Understanding Bayes theorem  does not  require a thorough understanding of the mathematics of probability calculations. More important is our capacity and desire to assign probability of truth and accuracy to everything we know or believe, as well as our willingness to change those probabilities when new information becomes available. Here is a little illustration of how I believe it works. 

Take, for example, the scenario in which you and a colleague have spent the afternoon playing your favorite board game and have reached the conclusion of the game and you are chit-chatting about this and that. In response to something he said, you decide to make a friendly wager: that with one roll of the die from the game, you will get a 6. Straight odds are one in six, resulting in a 16 percent probability of winning.

But imagine your colleague rolls the die, hastily covers it with his hand, and then sneaks a glance at the outcome. “I can tell you this much,” he continues, referring to the fact that the number is an even number.

Now that you have fresh knowledge, your odds shift dramatically, dropping to one in three, or a 33 percent probability. He  teasingly adds: “And it’s not a 4,” while you are debating whether or not to modify your wager.

After receiving this new piece of information, your odds have shifted once again, to one in two, or a 50 percent probability of success. Using this simple example, you have demonstrated your ability to do a Bayesian analysis.

The Bayesian approach is characterized by the fact that each new piece of information has an impact on the initial probability. 

According to Bayes’ theorem, we must continually update our probability estimates on an as-needed basis, and this is the core concept.

The Bayes’ theorem stands as a crucial reality check for our efforts to predict the future. while Bayes’ theorem can be a technical affair, like we experienced during the data analysis session, computing formulas, tables and numbers,  Bayesian reasoning can be used as a rule of thumb. We tend to either dismiss new evidence, or embrace it.  Bayesians attempt to assess both the old hypothesis and the new evidence in a raional way.

Just so I don’t risk leading you to believe that the Bayesian method will allow you to predict everything! I’d want to make a disclaimer.

We must acknowledge the limitations of inductive thinking in addition to viewing the world as an ever-changing array of probability.

A high probability that something is true does not indicate that it is true. So be comfortable with uncertainty and thrive on it. Instead of committing to obsolete ideas and rejecting new knowledge, assess what comes your way using a probabilistic framework.

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