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If someone asked you what power meant in easy-to-understand language, how would you respond?

What is the likelihood of four individuals on an elevator getting off on four different floors, given that the building they occupy has just four floors?

Describe your approach for joining two tables where one table has duplicates.

How would you approach calculating the expected spend of a 5$ coupon that was given to N users with a probability of P?

How does the size of the input data affect the time complexity of training an SVM? How is the time complexity for SVM inference calculated? Can you explain the effect of different kernels on the time complexity of SVMs?

When it comes to performance, do you think subqueries or joins are more efficient?

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?

How would you explain the concept of regression to a non-statistical professional?

In logistic regression, if two predictors are highly correlated, what impact does this have on the estimates of the regression coefficients and their confidence intervals?

Would you elucidate the meaning of training and loss graphs pertaining to neural networks? How does the choice of loss function impact the shape of the loss graph, and what are some extensively used ones? How do the training and loss graphs differ, and what role do they play in optimizing and maximizing model performance?