Calculate variance for coin flips

Last updated: January 3, 2026

Quick Overview

Given the following scenario about revenue per session, calculate the the p-value.

Bloomberg
Statistics & Math
Data Scientist
Bloomberg
January 3, 2026
Data Scientist
Technical Screen
Statistics & Math
Easy

113

8

3,098 solved


Given the following scenario about revenue per session, calculate the the p-value.

This statistics question from Bloomberg's Technical Screen tests your ability to apply mathematical reasoning to practical problems. The interviewer expects precise definitions, correct methodology, and awareness of assumptions and limitations.

What the Interviewer Expects
  • State the correct formula or theorem with clear definitions
  • Apply the concept to the given scenario step by step
  • Interpret the result in plain language
  • Identify assumptions and when they might be violated
Key Topics to Cover
Power analysis and sample size calculation
Multiple testing correction (Bonferroni, FDR)
Hypothesis testing (H0, H1, p-values)
Probability distributions
Conditional probability and Bayes theorem
Causal inference basics
How to Approach This
  1. Define your hypotheses (H0 and H1) clearly before performing any test.
  2. Calculate required sample size BEFORE running an experiment, using power analysis.
  3. Remember the Central Limit Theorem: sample means become approximately normal with large n.
  4. Watch for Simpson's paradox. Always segment data by key dimensions.
  5. Distinguish between statistical significance and practical significance.
Possible Follow-up Questions
  • How would you design a follow-up experiment based on these results?
  • How would you explain this result to a non-technical audience?
  • How would you handle multiple comparisons?
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Sample Answer
Problem Formulation

We need to calculate the variance of the revenue per session derived from flipping a fair coin. In this scenario, let 'X' represent the outcome of a single coin flip where 'X = 1' indicates a 'heads' ...

Solution Approach

To compute the variance, we apply the formula for the variance of a binomial distribution: Var(X) = n * p * (1 - p). Here, we need to determine the values of 'n' and 'p'. For example, if we assume we ...


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