Statistical analyst interview questions shared by candidates
You have 1000 randomly sampled data points. The goal is to try to build a regression model with one response variable from k regressor variables. Which is better? 1. (Bayesian Regression) Using the first 500 samples to estimate the parameters of an assumed prior distribution and then use the last 500 samples to update the prior to a posterior distribution with posterior estimates to be used in the final regression model. 2. (OLS Regression) Use a simple ordinary least squares regression model with all 1000 regressor variables.
2 is best under most assumptions
A company that produces an inexpensive frozen pizza product (eaten mostly by children) is experiencing losses in sales and the grocery stores that carry the product are threatening to remove it from shelves. The company is considering at least two options: A) Begin a television advertising campaign for the current frozen pizza product targeting children after school, and B) In addition to the current frozen pizza, start to produce a new product, the "pizza pocket," which would be the first of its kind and does not have any current competitors. What are the pros and cons of each option? Walk through the processes of how you would decide whether to recommend either option to the company.
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