Implement bootstrap mean and variance
Company: Airwallex
Role: Data Scientist
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Onsite
Given an array of N numeric values, implement a function that uses bootstrap resampling to estimate the sampling distribution of the mean.
The function should:
- take as input the array and the number of bootstrap resamples B,
- for each resample, draw N observations with replacement from the original array,
- compute the mean of each resampled array, and
- return:
1. the bootstrap estimate of the mean of the sample mean, and
2. the bootstrap estimate of the variance of the sample mean.
Assume the input array fits in memory and do not use built-in bootstrap utilities.
Quick Answer: This question evaluates a candidate's ability to implement bootstrap resampling and compute statistical estimates for the sampling distribution of the mean, testing skills in resampling methods, numerical computation, and statistical inference.