Bayes' Theorem Part-4 -- Example

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Part-1:

The Bayes’ Theorem - An Introduction

The Bayes’ Theorem - An Introduction In statistics and applied mathematics , the Bayes’ theorem also referred to as the Bayes’ rule may be a mathematical formula wont to determine the contingent probability of events. Essentially, the Bayes’ theorem describes the probability of an occasion supported prior knowledge of the conditions which may be relevant to the event. The theorem is known as after english statistician, Bayes , who discovered the formula in 1763. it’s considered the inspiratio…

Part-2:

Bayes' Theorem Part-2 -- Intuitive understanding

If not following the conversation and missed the previous post, please referred the below link to understand the former definition of Bayes’ Theorem. Bayes’ Theorem Part-2 – Intuitive understanding The man was sitting together with his back to a wonderfully flat and perfectly square table. Then he asked his assistant to throw the ball on the table. Obviously, this ball could have landed and ended up but during a more analytical way. So, he asked his assistant to throw another ball on the t…

Part-3:

Bayes' Theorem Part-3 -- Explanation

If you are not following the conversation series the previous post, please referred the below link. Part-1 Link: Part-2 Link: Bayes’ Theorem Part-3 – Explanation [image] Image Credit: (https://luminousmen.com/post/data-science-bayes-theorem) Above image we’ve two overlapped events A and B. It can be, for instance A — i buy wet today, B — it’ll be rainy today. In a method or another, many events are associated with one another , as in our example. Let’s calculate the probability of A a…

Bayes’ Theorem Part-4 – Example

Assume you’re a securities analyst at an investment bank. consistent with your research of publicly-traded companies, 60% of the businesses that increased their share price by quite 5% within the last three years replaced their CEOs during the amount .

At an equivalent time, only 35% of the businesses that didn’t increase their share price by quite 5% within the same period replaced their CEOs. Knowing that the probability that the stock prices grow by quite 5% in 4%, find the probability that shares of a corporation that fires its CEO will increase by quite 5%.

Before finding the probabilities, you must first define the notation of the probabilities.

• P(A) — the probability that the stock price increases by 5%.
• P(B) — the probability that the CEO is replaced.
• P(A|B) — the probability of the stock price increases by 5% given that the CEO has been replaced.
• P(B|A) — the probability of the CEO replacement given the stock price has increased by 5%.

Using the Bayes’ theorem , we will find the specified probability:

Thus, the probability that the shares of a corporation that replaces its CEO will grow by quite 5% is 6.67% probability.

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