G
Ganardo
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The standard deviation of a typical lottery game is a measure of how much the winnings deviate from the expected value, indicating the variability and risk associated with the game. To calculate the standard deviation for a lottery game, one must consider the probabilities of different outcomes and their respective payouts.
Key Concepts
1. Expected Value (EV):
- This is the average amount one can expect to win (or lose) per ticket in the long run. It's calculated by summing the products of each possible outcome's value and its probability.
2. Variance:
- Variance measures the spread of the winnings around the expected value. It is calculated by summing the squared differences between each outcome's value and the expected value, each weighted by its probability.
3. Standard Deviation (σ):
- The standard deviation is the square root of the variance, providing a measure of the spread in the same units as the original payouts.
Calculation Example
Let’s consider a simple hypothetical lottery with the following characteristics:
- Ticket price: $2
- Possible outcomes:
- Jackpot: $1,000,000 (probability: 1 in 10,000,000)
- Small prize: $50 (probability: 1 in 100,000)
- No prize: $0 (probability: the remaining probability)
Step-by-Step Calculation:
1. Determine Probabilities and Payouts:
- Jackpot: \( P_1 = \frac{1}{10,000,000} \), payout = $1,000,000
- Small prize: \( P_2 = \frac{1}{100,000} \), payout = $50
- No prize: \( P_3 = 1 - P_1 - P_2 \), payout = $0
2. Calculate Expected Value (EV):
- \( EV = (P_1 \times 1,000,000) + (P_2 \times 50) + (P_3 \times 0) - \text{Ticket Price} \)
- \( EV = \left(\frac{1}{10,000,000} \times 1,000,000\right) + \left(\frac{1}{100,000} \times 50\right) + (0) - 2 \)
- \( EV = 0.1 + 0.0005 - 2 = -1.8995 \)
3. Calculate Variance:
- Variance \( \sigma^2 \) = \(\sum P_i \times (V_i - EV)^2\)
- For each outcome:
- Jackpot: \( P_1 \times (1,000,000 + 1.8995)^2 \)
- Small prize: \( P_2 \times (50 + 1.8995)^2 \)
- No prize: \( P_3 \times (-1.8995)^2 \)
- Plugging in values:
- \( \sigma^2 = \left(\frac{1}{10,000,000} \times (1,000,000.1)^2\right) + \left(\frac{1}{100,000} \times (51.8995)^2\right) + \left((1 - \frac{1}{10,000,000} - \frac{1}{100,000}) \times (-1.8995)^2\right) \)
4. Calculate Standard Deviation (σ):
- Standard deviation \( \sigma = \sqrt{\sigma^2} \)
The actual calculations involve complex arithmetic but generally result in a high standard deviation due to the large payouts and the low probability of winning.
The standard deviation of a typical lottery game tends to be quite high because of the large disparity between the low probability of winning significant prizes and the high probability of losing (or winning small amounts). This high variability reflects the high risk associated with playing lotteries, reinforcing the understanding that while the potential rewards can be substantial, the chances of winning are low and outcomes are highly unpredictable.
Key Concepts
1. Expected Value (EV):
- This is the average amount one can expect to win (or lose) per ticket in the long run. It's calculated by summing the products of each possible outcome's value and its probability.
2. Variance:
- Variance measures the spread of the winnings around the expected value. It is calculated by summing the squared differences between each outcome's value and the expected value, each weighted by its probability.
3. Standard Deviation (σ):
- The standard deviation is the square root of the variance, providing a measure of the spread in the same units as the original payouts.
Calculation Example
Let’s consider a simple hypothetical lottery with the following characteristics:
- Ticket price: $2
- Possible outcomes:
- Jackpot: $1,000,000 (probability: 1 in 10,000,000)
- Small prize: $50 (probability: 1 in 100,000)
- No prize: $0 (probability: the remaining probability)
Step-by-Step Calculation:
1. Determine Probabilities and Payouts:
- Jackpot: \( P_1 = \frac{1}{10,000,000} \), payout = $1,000,000
- Small prize: \( P_2 = \frac{1}{100,000} \), payout = $50
- No prize: \( P_3 = 1 - P_1 - P_2 \), payout = $0
2. Calculate Expected Value (EV):
- \( EV = (P_1 \times 1,000,000) + (P_2 \times 50) + (P_3 \times 0) - \text{Ticket Price} \)
- \( EV = \left(\frac{1}{10,000,000} \times 1,000,000\right) + \left(\frac{1}{100,000} \times 50\right) + (0) - 2 \)
- \( EV = 0.1 + 0.0005 - 2 = -1.8995 \)
3. Calculate Variance:
- Variance \( \sigma^2 \) = \(\sum P_i \times (V_i - EV)^2\)
- For each outcome:
- Jackpot: \( P_1 \times (1,000,000 + 1.8995)^2 \)
- Small prize: \( P_2 \times (50 + 1.8995)^2 \)
- No prize: \( P_3 \times (-1.8995)^2 \)
- Plugging in values:
- \( \sigma^2 = \left(\frac{1}{10,000,000} \times (1,000,000.1)^2\right) + \left(\frac{1}{100,000} \times (51.8995)^2\right) + \left((1 - \frac{1}{10,000,000} - \frac{1}{100,000}) \times (-1.8995)^2\right) \)
4. Calculate Standard Deviation (σ):
- Standard deviation \( \sigma = \sqrt{\sigma^2} \)
The actual calculations involve complex arithmetic but generally result in a high standard deviation due to the large payouts and the low probability of winning.
The standard deviation of a typical lottery game tends to be quite high because of the large disparity between the low probability of winning significant prizes and the high probability of losing (or winning small amounts). This high variability reflects the high risk associated with playing lotteries, reinforcing the understanding that while the potential rewards can be substantial, the chances of winning are low and outcomes are highly unpredictable.