As a data analyst, you might need to use probability distribution for several reasons:
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To discover meaningful relationships between events.
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To make better data-driven decisions by answering questions like 'how likely something has happened out of pure coincidence'.
In the discrete.ipynb
file you can find exercises on Bernoulli's, binomial, and poisson distributions. In the continuous.ipynb
file you can find exercises on uniform, normal, and exponential distributions. In each exercise please read the question carefully and provide your solutions below the question. All the calculations must be performed using Python. The dataset to be used in the exercise has been provided on GitHub here. Also please keep in mind that you might also need to use some of the functions you saw in the previous lessons. Please refer the notes.
Happy Learning!!
discrete.ipynb
with your responses.continuous.ipynb
with your responses.
Upon completion, add your deliverables to git. Then commit git and push your branch to the remote.
Probability distribution cheat sheet