calculates the returns as the percentage change in the ‘Close’ column of the input
DataFrame, and then drops the first row, which will have a NaN return. Finally, the Jarque-Bera test for
normality is performed on the returns using the <cite>jarque_bera</cite> function from the <cite>scipy.stats</cite> module.
The test statistic and p-value are returned as a tuple.</p>
<p>The null hypothesis of the Jarque-Bera test is that the sample of data being tested is drawn from a normal
distribution. Therefore, a