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I have been studying Bayesian statistics recently. Monte Carlo simulations are a large part of Bayesian statistics, so I have been studying that as well.
One major part of Monte Carlo simulations is the random walk, which I have studies in the past, but have decided to revisit within the context of Bayesian statistics.
I have previously created a Monte Carlo random walk in Excel and wanted to convert it to Python and then R to see the similarities and differences between these platforms.
In order to save time I asked copilot if it could make a random walk in Python, and it responded with code in Python that provided the resulting graph:-
I have seen this image and the code related to it in the past, so I did not feel comfortable using it. In addition, this particular random walk provided 1,000 random walks of 100 steps each when I only wanted one. In addition, it did not provide any metrics, such as the mean and variance of a random walk. And lastly, I did not provide any autocorrelation coefficient, which is what was included in the random walk that I had created in Excel.