probability of outcome in small sample size

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I read about the law of small numbers (psychological phenomenon related to the statistical law of large numbers), where the following example is given:

Suppose a drug is effective in 80% of patients. If five patients are treated, how many will respond?

Many people reason that 80% means 4 out of 5, so if 5 people are treated, exactly 4 will respond. Always.

Others understand that things are not guaranteed to work out so neatly, but they still believe that it is highly likely that 4 people would respond. Maybe a 90% chance.

In fact, there’s only a 41% chance that exactly 4 would respond out of a sample of 5.

Can someone explain how they got to 41%, by way of example:

If there is a 50% chance of heads and you flip 10 times whats the chance that you get 5 heads?

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The number of patients who respond to the treatment follows a Binomial distribution with $n=5$ and $p=0.8$. The probability of exactly four patients responding is $$ {5 \choose 4} \times 0.8^4 \times 0.2 = 0.4096 $$