Run the following code in a Jupyter code cell:

from scipy.stats import norm
mmean, msdev = 70, 4.0
fmean, fsdev = 65, 3.5
mdist = norm(mmean, scale=msdev)
fdist = norm(fmean, scale=fsdev)
nm, nf = 2000, 1500
mdata = mdist.rvs(size=nm)
fdata = fdist.rvs(size=nf)
plt.figure(figsize=(12, 4))
plt.subplot(1,2,1)
plt.hist([mdata, fdata], bins=20,
         label=['Males', 'Females'])
plt.legend()
plt.xlabel('Height (inches)')
plt.ylabel('Frequency')
plt.subplot(1,2,2)
plt.boxplot([mdata, fdata], patch_artist=True,
            labels=['Males', 'Females'])
None

Running this code will generate the following graph:

The two graphs clearly display the characteristics of a normal distribution, with heights for the male population having a larger mean and standard deviation. The box plots also display the outliers in the distribution, according to the 1.5 IQR rule.