If you not following the conversation, please feel free to referred the below links.

Part-1:

Part-2:

Part-3:

#
**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.

Please feel free to comment your thoughts on this and follow this conversation series for intuitive content ahead.

Make sure give a like if you are reading the conversation for support and motivation.