Implementing Probability Basics in Python
Probability concepts are the foundation of analyzing uncertain events.
Here we learn how to compute union and intersection using a simple dice example.
Defining Sample Space and Events
# Small numbers on a die
A = {1, 2, 3}
# Even numbers on a die
B = {2, 4, 6}
die_outcomes = 6
Here we define:
- A={1,2,3} representing "small" outcomes;
- B={2,4,6} representing "even" outcomes.
The total number of die outcomes is 6.
Performing Set Operations
12345678# Small numbers on a die A = {1, 2, 3} # Even numbers on a die B = {2, 4, 6} die_outcomes = 6 print(f'A and B = {A & B}') # {2} print(f'A or B = {A | B}') # {1, 2, 3, 4, 6}
- The intersection A∩B={2} → common element.
- The union A∪B={1,2,3,4,6} → all elements in A or B.
Calculating Probabilities
123456789101112131415161718# Small numbers on a die A = {1, 2, 3} # Even numbers on a die B = {2, 4, 6} die_outcomes = 6 A_and_B = A & B # {2} A_or_B = A | B # {1, 2, 3, 4, 6} P_A = len(A) / die_outcomes P_B = len(B) / die_outcomes P_A_and_B = len(A_and_B) / die_outcomes P_A_or_B = P_A + P_B - P_A_and_B print("P(A) =", P_A) print("P(B) =", P_B) print("P(A ∩ B) =", P_A_and_B) print("P(A ∪ B) =", P_A_or_B)
We use the formulas:
- P(A)=6∣A∣=63;
- P(B)=6∣B∣=63;
- P(A∩B)=6∣A∩B∣=61;
- P(A∪B)=P(A)+P(B)−P(A∩B)=65.
Additional Set Details
12345only_A = A - B # {1, 3} only_B = B - A # {4, 6} print(only_A) print(only_B)
- Elements only in A: {1, 3};
- Elements only in B: {4, 6}.
1. What is the output of this code?
2. What does this line compute?
3. What is the result of this code?
4. Which line correctly calculates the union probability using Python?
5. What does this code return?
Alt var klart?
Takk for tilbakemeldingene dine!
Seksjon 5. Kapittel 2
Spør AI
Spør AI
Spør om hva du vil, eller prøv ett av de foreslåtte spørsmålene for å starte chatten vår
Awesome!
Completion rate improved to 1.89
Implementing Probability Basics in Python
Sveip for å vise menyen
Probability concepts are the foundation of analyzing uncertain events.
Here we learn how to compute union and intersection using a simple dice example.
Defining Sample Space and Events
# Small numbers on a die
A = {1, 2, 3}
# Even numbers on a die
B = {2, 4, 6}
die_outcomes = 6
Here we define:
- A={1,2,3} representing "small" outcomes;
- B={2,4,6} representing "even" outcomes.
The total number of die outcomes is 6.
Performing Set Operations
12345678# Small numbers on a die A = {1, 2, 3} # Even numbers on a die B = {2, 4, 6} die_outcomes = 6 print(f'A and B = {A & B}') # {2} print(f'A or B = {A | B}') # {1, 2, 3, 4, 6}
- The intersection A∩B={2} → common element.
- The union A∪B={1,2,3,4,6} → all elements in A or B.
Calculating Probabilities
123456789101112131415161718# Small numbers on a die A = {1, 2, 3} # Even numbers on a die B = {2, 4, 6} die_outcomes = 6 A_and_B = A & B # {2} A_or_B = A | B # {1, 2, 3, 4, 6} P_A = len(A) / die_outcomes P_B = len(B) / die_outcomes P_A_and_B = len(A_and_B) / die_outcomes P_A_or_B = P_A + P_B - P_A_and_B print("P(A) =", P_A) print("P(B) =", P_B) print("P(A ∩ B) =", P_A_and_B) print("P(A ∪ B) =", P_A_or_B)
We use the formulas:
- P(A)=6∣A∣=63;
- P(B)=6∣B∣=63;
- P(A∩B)=6∣A∩B∣=61;
- P(A∪B)=P(A)+P(B)−P(A∩B)=65.
Additional Set Details
12345only_A = A - B # {1, 3} only_B = B - A # {4, 6} print(only_A) print(only_B)
- Elements only in A: {1, 3};
- Elements only in B: {4, 6}.
1. What is the output of this code?
2. What does this line compute?
3. What is the result of this code?
4. Which line correctly calculates the union probability using Python?
5. What does this code return?
Alt var klart?
Takk for tilbakemeldingene dine!
Seksjon 5. Kapittel 2