Replaced numpy.random with the new random generator

[KavyaJaiswal]

Description

File: https://github.com/pymc-devs/pymc-examples/blob/main/examples/generalized_linear_models/GLM.ipynb

Addresses issue #91 and aims to advance the notebook to the 'Best Practices' State.

The new code uses the new numpy generator instead of the numpy random. The code also has a ArviZ related addition of return_inferencedata=True

The PR has a (commented) try... except clause in the code. On un-commenting, it will ensure that users who have cloned pymc-examples repo will read their local copy of the data while also downloading the data from github for those who don't have a local copy.

try:
    sat_data = pd.read_csv("../data/Guber1999data.txt", ...)
except:
    sat_data = pd.read_csv(pm.get_data("Guber1999data.txt"), ...)

This PR also addresses the error message in the Hierarchical GLM section of the code. The error in the code is shown in the screenshots attached below. The fix for this error can be discussed and worked upon.

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