# Solved – How to check if a data set can be modelled by a normal distribution

I have a set of velocity data (37 data points) and I want to know how to check if the data can be modelled with a normal distribution.

From a guide on youtube I have calculated the CDF, expected values and Z-values and produced a plot of the expected values and real data against the z-values.

From here I'm lost as what to do next, how do I determine how well the data is modelled by a normal distribution from this plot? Some of the real data points lie above the line and some below and it seems to fit reasonably well but
I would like to be more quantitative about it.

Please bear in mind I know only basic statistics and this has already gone way beyond my knowledge.

Contents

Here is a Wikipedia article on it.

In summary:

You can look at a histogram of the data, does the shape look similar to a normal distribution? You can look at quantile-quantile plots (Q-Q plots), do the sample quantiles of your data match up to the theoretical quantiles of a normal distribution?

You can do a hypothesis test to formally test this (Shapiro-Wilk test, etc)

What software do you use? I can show you specific examples of how to do the above mentioned techniques.

Here is a nice excel video for QQ plots

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