Basic Statistics in Python — Probability

Probability is the chance of an event to happen , we also need to consider all the other events that can occur .

As the number of randomized trials increases, the average calculated ratio will approach the expected ratio

the data confirm that our average number of heads does approach what probability suggests it should be. Furthermore, this average improves with more trials.

the normal distribution is a particular distribution of the probability across all of the events. The x-axis takes on the values of events we want to know the probability of. The y-axis is the probability associated with each event, from 0 to 1. The high point in a statistical context represents the mean.

Central Limit Theorem  Central Limit Theorem lets us know that the average of many trials means will approach the true mean, the Three Sigma Rule will tell us how much the data will be spread out around this mean.

Three Sigma Rule The Three Sigma rule dictates that given a normal distribution, 68% of your observations will fall between one standard deviation of the mean. 95% will fall within two, and 99.7% will fall within three. A lot of complicated math goes into the derivation of these values

Z-score The Z-score dictates that how many standard deviations is it away from the mean?” The equation below is the Z-score equation.