The underlying probability distribution can't be determined with certainty in this case from the given data, but if we have to take one it would be most preferably the 'Normal Distribution'.
Step-by-step explanation:
The distribution is most probably 'Normal Distribution' as we know that it is the most general and common distribution of all and from the central limit theorem if there is a large sample from any probability distribution with finite mean and variance, the sample mean approaches a suitable normal distribution and for most of the distributions when the parameters tend to a certain value or may be that is ∞ , the resulting distribution tends to a suitable normal distribution , but the underlying probability distribution can't be determined with certainty in this case from the given data.
