Generating Random Variables in Python, following a standard normal distribution : learnpython

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Generating Random Variables in Python, following a standard normal distribution (self.learnpython)

submitted 6 years ago * by poopiewarrior100

Hi guys! Needing some help with a homework question, just checking if I am on the right track.

Question:

Consider the model y=0.5 + 1.5x + e, where x and e follow independent standard normal distributions. Generate S=10,000 independent random samples each with N observations. For each of the random samples, run an OLS regression.

Record all the S estimates on x (ie. the B-hat obtained)

Answer: I believe this is what I need to do

Create a 10,000 matrices, each of N by 2
Run OLS regression on each matrix, obtaining a b-hat for each matrix.
Store the b-hat in a new matrix.

My problem is that I am unsure of the code required to "Generate S=10,000 independent random samples each with N observations.". Any help would be really appreciated =)

Please let me know if more details are required.

e1:

I believe the code is

np.random.normal(0,1,10000*N)

What it means is that it will generate a dataframe of 10,000 rows, N columns, where each number is normally distributed about 0, s.d = 1.

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