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You're drawing from a random variable that is normally distributed X ~ N(0,, once per day. What is the expected number of days that it takes to draw a value that's higher that 2?

What is the significance of the Wilk-Shapiro measure in detecting whether a dataset is normally distributed or not?

Have you ever encountered multicollinearity in your own work? How did you address it?

What's your understanding of the dissimilarities between the frequentist and Bayesian methods for probability? Further, what benchmarks would you use when selecting which path to take in a given situation?

What are your strategies for depicting data that has multiple dimensions?

What are your thoughts on feature selection and its significance within the realm of machine learning?

How do you see your career evolving in the next five years? Does Spotify fit into this plan?

How would you measure the effectiveness of a clustering model if the labels are available beforehand?

Could you describe the process for estimating the probability of ordering a ride, given a certain set of assumptions? What assumptions are necessary for this calculation? Furthermore, how would you generate a confidence interval for this probability?

What factors do you consider when selecting the correct statistical test for a problem?