Probability Distribution represents the probability of the outcome of an event. As the name says, it is the distribution of probabilities of all the outcomes of an event on a graph. In Data Science, it represents the dataset of outcomes on a graph; it helps in analyzing underlying trends in the data.
The distributed data represents the data on a frequency graph and to implement probability distribution we use random variables, which occur when the outcome is of a random event.
Possibilities Red(R),Blue(B) |
B,B |
R,R |
B,R |
R,B |
The illustration above shows the outcome of a random event; let's say we have a bag that contains four balls, 2 red balls, and 2 blue balls. The outcome of choosing 2 out of those 4 balls is presented in the illustration above.
Now let's say that we have to pick a red ball every time we draw balls from the bag and the probability of that event would be based on the number of red balls we are drawing.
Let's look into a probability distribution for drawing the red balls.
Outcomes | Probabilities |
B,B (both Blue) | 0.25 |
B,R/R,B (one Red, one Blue) | 0.50 |
R,R (both Red) | 0.25 |
Let's take a look at the graphical representation of the outcomes dataset on a bar plot.
It represents the probability of all the possible outcomes we have from our probability distribution function of drawing red balls. The probability of drawing one red ball is more than the probability of drawing both red balls and zero red balls.
Free Resources