My textbook has the following problem:
An airline claims that at most $6\%$ of all lost luggage is never found. A random sample of size $200$ is taken. Out of the $200$ observations (supposed to be independent) $23$ pieces of luggage were never found. Test whether the airline's claim is true at a $1\%$ significance level using the critical value method.
When identifying the probability model for this problem, the textbook uses a random variable with a Bernoulli distribution.
The same textbook defines Bernoulli random variables and Binomial random variables as follows:
Bernoulli Random Variables
A Bernoulli trial is an experiment which has two possible outcomes, generally called success and failure.
Binomial Random Variables
Let $X$ be the total number of successes in n repeated, independent Bernoulli trials with success probability $p$. $X$ is called the binomial random variable with parameters $n$ and $p$, written $X \sim Binom(n, p)$.
It seems to me like the problem should be using a Binomial random variable, since we have many (200) events, and we are seeking to find, out of those 200, how many pieces were lost (failure) and how many were not (success). I certainly do not see how using a Bernoulli random variable is correct in such a situation.
I would greatly appreciate it if people could please take the time to clarify this for me.