First, to understand the reason to use a normal distribuition, let's analyse some of it's properties.
The normal distribution is given by the following formula:
![f(x)\text{ = }\frac{1}{\sigma\sqrt[]{2\pi}}\text{exp\lbrack}(-1)/(2)((x-\mu)/(\sigma))^2\text{ \rbrack}](https://img.qammunity.org/2023/formulas/mathematics/high-school/akenx1wf34qbthuer3lc45vmniew5dtzpm.png)
The normal distribuition is centered at the mean(given by 'mu' in the equation above) and its growth is controlled by its standard deviation(given by the 'sigma').
It is shaped like a bell(centered, with a gaussian decay, symetric). The data given by the question, have all of those properties. Is centered at the middle with a exponential decay in both 'directions'. Since the data agrees with the gaussian distribution properties, it makes sense to model this distribuition as a normal distribuition.