Expected value calculations

Advanced Probability: Uncertainty in Data

Maarten Van den Broeck

Senior Content Developer at DataCamp

What is expected value?

  • Weighted average
  • Expectation over time
  • Take into account multiple possibilities

Tip jar

Advanced Probability: Uncertainty in Data

How expected value calculations work

  1. Identify possible outcomes
  2. Assign probabilities
  3. Calculate the expected value
  4. Interpret the results and make a decision

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  • On average, you will lose money if you keep buying lottery tickets!
  • A lottery ticket: win (USD 1,000) or lose the ticket price (USD 2)
  • Winning: 0.1%, losing: 99.9%
  • Expected value:

$(0.001*1000)+(0.999*2) = -1$

Advanced Probability: Uncertainty in Data

Expected value calculations in practice

  • Bigger picture: possibilities and their probabilities
  • Balance risk and reward
  • Example applications:
    • Set product prices
    • Assess financial impact of different strategies
    • Compare profitability of stock options

Balancing

Advanced Probability: Uncertainty in Data

How are probabilities for expected values determined?

  • Historical data analysis:
    • Past trends provide probabilities
  • Market research and surveys:
    • Market data provides probabilities
  • Expert judgment:
    • Expert estimations provide probabilities

Data and research

Advanced Probability: Uncertainty in Data

Example: pricing decisions

Demand Units Sold Probability Revenue ($)
High 1000 30% 50,000
Moderate 700 50% 35,000
Low 400 20% 20,000
Total Expected Revenue 36,500

 

  • Company can:
    • Compare expected revenue to break-even point
    • Reconsider pricing strategy
Advanced Probability: Uncertainty in Data

Let's practice!

Advanced Probability: Uncertainty in Data

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