Misprints per page of a thick book follow Poisson distribution.

Explanation:

Poisson Distribution is used to model the number of occurrences of an event in a fixed interval of time or space. The characteristics of Poisson distribution are:

- The events occur independently of each other.
- The average rate of occurrence is constant.
- The probability of the event occurring in a small interval is proportional to the size of the interval.

In the case of misprints per page of a thick book, we can assume that the occurrence of misprints on one page is independent of the occurrence of misprints on any other page. Additionally, the average rate of misprints per page is constant throughout the book. Finally, the probability of a misprint occurring on a page is proportional to the size of the page.

Therefore, we can use Poisson distribution to model the number of misprints per page of a thick book.

Other distributions that can be used to model the number of misprints per page of a thick book are:

- Normal distribution: This distribution is used to model continuous data that follow a bell-shaped curve. However, the number of misprints per page is a discrete variable that can only take non-negative integer values, so normal distribution is not appropriate.
- Binomial distribution: This distribution is used to model the number of successes in a fixed number of trials. However, in the case of misprints per page, there is no fixed number of trials, so binomial distribution is not appropriate.
- Standard normal distribution: This distribution is a special case of normal distribution where the mean is 0 and the standard deviation is 1. However, as mentioned above, normal distribution is not appropriate for modeling the number of misprints per page of a thick book.

Answer is poison distribution because they have given number of misprints and this is something which tends to infinite and the event is unknown as we don't know the exact n value as we can know easily in case of binomial distribution though it is infinite it falls under discrete random variable which is a countable infinite number...Hope this helps you :-)