Data Science different topic's explanation -- Part-6 -- Marginal Probability and Conditional Probability

This is data science different topic explanation conversation series.
If you are not following below mentioned are the links for each part.






Data Science different topic’s explanation – Part-6 – Marginal Probability and Conditional Probability

Marginal Probability

Marginal Probability – a probability of any single event occurring unconditioned on any other events.

Whenever someone asks you whether the weather is going to be rainy or sunny today (without any conditional or prior information), you are computing a marginal probability.

Conditional Probability

Conditional probability – is a probability of an event given that (by assumption, presumption, assertion, or evidence another event has occurred.

When i ask you what is the probability that today will be rainy or sunny given that i notices the temperature is going to be above 80 F, you are computing a conditional probability.

So, we want to understand the probability of event B given A. It is defined as the probability of the joint of events A and B divided by the probability of B. Thus,

Continuing the above post, what ever i missed out.

Example: A math teacher gave her class two tests. 25% of the class passed both tests and 42% of the class passed the first test. What is the probability of those who passed the first test also passed the second test?

Next Post: Probability Distributions