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Day 10: Understanding Probability: From Basics to Conditional

A Deep Dive into Probability with Real-Life Examples

What is Probability?

Basic Definition

Probability is the likelihood or chance of an event occurring. It's the ratio of:

Probability = Favorable outcomes / Total possible outcomes

Probability always ranges from 0 (impossible) to 1 (certain)

Probability Scale

0% 25% 50% 75% 100%
Impossible Unlikely Equal chance Likely Certain

Simple Examples:

  1. Coin Toss:
    • Getting heads: 1/2 = 0.5 = 50%
    • Getting tails: 1/2 = 0.5 = 50%
  2. Playing Cards:
    • Drawing an ace: 4/52 = 1/13 ≈ 7.7%
    • Drawing a heart: 13/52 = 1/4 = 25%

Understanding Conditional Probability

What Makes it "Conditional"?

Conditional probability is the likelihood of an event occurring, given that another event has already occurred.

P(A|B) = P(A and B) / P(B)

Read as: "Probability of A, given that B has occurred"

Real-Life Example: Weather and Traffic

Let's break down why traffic is more likely on rainy days:

Scenario Probability
Chance of rain any day 30% = 0.3
Traffic on a normal day 80% = 0.8
Traffic when it rains 100% = 1.0

Why This Matters:

  • Normal traffic probability: 80%
  • But if it's raining (condition), traffic probability jumps to 100%
  • The rain condition changes the probability

Another Example: Biryani Orders

Understanding delivery success based on conditions:

Condition Regular Day Rainy Day
Delivery on time 90% 70%
Food hot on arrival 95% 80%

The weather condition affects both delivery time and food temperature!

Key Points to Remember

  • Basic Probability:
    • Always between 0 and 1 (or 0% to 100%)
    • All possible outcomes must sum to 1 (100%)
    • Independent events don't affect each other
  • Conditional Probability:
    • One event depends on another
    • Changes based on known conditions
    • Helps predict real-world scenarios better

Practice Problem Set: The Food Delivery Challenge

Scenario Setup

You run a food delivery service in Hitech City with the following data:

  • Total Orders per day: 100
  • Biryani orders: 40%
  • Peak hour orders (6-8 PM): 50%
  • Biryani orders during peak hours: 25 orders

Question 1: Basic Probability

What's the probability of a random order being a biryani order?

Solution:

  • Total orders = 100
  • Biryani orders = 40
  • Probability = 40/100 = 0.4 or 40%

Question 2: Conditional Probability

If an order comes during peak hours, what's the probability it's a biryani order?

Solution:

  • Peak hour orders = 50
  • Biryani orders during peak hours = 25
  • P(Biryani|Peak) = 25/50 = 0.5 or 50%

Question 3: Complex Scenario

Given these additional conditions:

  • Delivery success rate on normal days: 95%
  • Rainy days in a month: 6 days
  • Delivery success rate on rainy days: 80%

What's the probability of a successful delivery on a rainy day for a peak hour biryani order?

Step-by-Step Solution:

  1. First, identify the events:
    • A: Successful delivery
    • B: Rainy day
    • C: Peak hour biryani order
  2. We know:
    • P(A|B) = 80% = 0.8 (success rate on rainy days)
    • P(C|B) = 50% = 0.5 (peak hour biryani probability)
  3. Final Probability = 0.8 × 0.5 = 0.4 or 40%

Bonus Challenge: The Biryani Piece Probability

At Shah Gouse:

  • Each biryani has 3 pieces
  • 60% are leg pieces
  • 30% are breast pieces
  • 10% are wing pieces

If you order 2 biryanis, what's the probability of getting at least one leg piece?

Solution:

  1. First, find probability of NOT getting a leg piece in one biryani
    • P(no leg) = 0.4
  2. Probability of no leg pieces in both biryanis
    • P(no leg in both) = 0.4 × 0.4 = 0.16
  3. Therefore, probability of at least one leg piece
    • P(at least one leg) = 1 - 0.16 = 0.84 or 84%

Key Learning Points

  • Basic probability deals with independent events
  • Conditional probability considers related events
  • Real-world scenarios often involve multiple conditions
  • Breaking down complex problems into simple steps helps