In today’s modern world, Probability and Statistics play a crucial role in our everyday life. It helps in representing the complicated data in a very clear and precise manner. It is a tool used by many researchers, sports analysts, health care workers and many more to make decisions according to the uncertainity.
Speaking of probability, the first thing that comes to mind is, the probability of getting a head while tossing a coin or the probability of throwing a dice and getting a specific number like 1 or 6 at a time.
But we also use probability in our day-to-day lives. For example,
So probability is measuring the uncertainty or measuring the certainity that an event will happen, as it also helps in predictions and decision making choices.
In this blog we are going to deep dive and discuss what probability is, where it is used, the math concept, the basics of probability to start off with this journey and then some important distributions that come into play in the Machine learning and Data Science field.
Probability is how strongly we believe that an event will happen. The simple way to understand probability is to express it as percentages.
For example - The probability of winning the lottery is 70%.
$$ P(X) = 70\% = 0.70 $$
Here, P(X) —> Probability of winning the lottery, which means there is a 70% chance of winning the lottery and 30% chance of not winning it.