Probability In statistics


Basic idea

Experiment: a process the results in an outcome that cannot be predicted in advance with certainty.

Toss a Coin

S = {H,T}

Sample space: set of all possible outcomes

Rolling a die

S = {1,2,3,4,5,6}

Event: subset of the sample space

Back to the examples:

Let even A be the roll of 1, A={1} Let event E be an even role, E={2,4,6}


Up to this point, you have been a “frequentist

Plugging in the numbers:

Basic Axioms:

Axioms are the basic building blocks of probability theory.

Here are the three basic axioms:

P(a) is greater than or equal to 0, but less than or equal to 1 for all events a

P(S) is equal to 1

P(A or B) = P(A) + P(B) - P(A and B)

Ven Diagrams

Setting up the environment:

import micropip
await micropip.install("matplotlib")
await micropip.install("matplotlib_venn")
 
import matplotlib.pyplot as plt
from matplotlib_venn import venn2
 
# Data
labels = ['A', 'B', 'A and B']
 
 
plt.figure(figsize=(6, 4))
  1. Not in A
venn2(subsets=(1, 0, 0), set_labels=labels)
plt.title('Not in A')
plt.show()
  1. Not in B
venn2(subsets=(0, 1, 0), set_labels=labels)
plt.title('Not in B')
plt.show()
  1. A and B
venn2(subsets=(0, 0, 1), set_labels=labels)
plt.title('A and B')
plt.show()
  1. A or B
venn2(subsets=(1, 1, 1), set_labels=labels)
plt.title('A or B')
plt.show()
  1. DeMorgans Law

DeMorgan’s Law states that the complement of the union of two sets is equal to the intersection of the complements of the two sets.

venn2(subsets=(1, 1, 0), set_labels=labels)
plt.title("DeMorgan's Law")
plt.show()

Lets examine the ideas DeMorgans Law presents.

Quantification vs Complement

QuantificationComplement
All 5Not all 0, 1, 2, 3, 4
1,2,3,4,5Not some

Are events mutually exclusive?

Depends on the problem.

Lets look at a deck of cards:

Deck of Cards

S = {52 cards} A = {red cards} B = {face cards} A and B = {red face cards}

Are A and B mutually exclusive?

No, because there are red face cards.

The intersection of A and B is not empty.