= \$0.02$. So expected profit is roughly $\
- 0.02 - 0.02 \times 2 = \.94$. Let's be precise.
Formal Solution:
Let $D$ be the event that a widget is defective. We have $P(D) = 1/50$ and $P(D^c) = 49/50$.
The profit $X$ for a single widget is: - $X = +2$ if not defective (probability $49/50$) - $X = -1$ if defective (probability
/50$)
The expected profit is:
$E[X] = 2 \cdot \frac{49}{50} + (-1) \cdot \frac{1}{50} = \frac{98}{50} - \frac{1}{50} = \frac{97}{50} = 1.94$
Answer: The expected profit per widget is $\
.94$.
Intuition
This is about as basic as expected value gets, but it illustrates an important principle: even a small defect rate has a measurable impact on expected profit. Here the
\%$ defect rate knocks $\$0.06$ off the $\
$ ideal profit -- a $3\%$ haircut. In manufacturing and trading alike, the key insight is that the expected cost of rare bad outcomes is (probability) times (severity), and you should always do this multiplication explicitly rather than dismissing low-probability events as negligible.
In a quant context, this same structure appears everywhere: expected P&L from a trade is (probability of winning) times (win size) minus (probability of losing) times (loss size). The widget problem is just the simplest version of that calculation.
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