Interpret a statistically significant lift of 2% from an experiment

Last updated: May 7, 2026

Quick Overview

An experiment shows conflicting results. What conclusions can you draw? What are the caveats?

Square/Block

Statistics & Math

Data Scientist

Square/Block

May 7, 2026

Data Scientist

Take-home Project

Statistics & Math

Medium

563 solved

An experiment shows conflicting results. What conclusions can you draw? What are the caveats?

Statistics questions at Square/Block test your ability to reason quantitatively and design rigorous experiments. This Take-home Project question evaluates your understanding of statistical inference and its application to business decisions.

What the Interviewer Expects

Set up the problem formally with proper notation
Apply the correct statistical test with clear justification
Interpret results with appropriate caveats and confidence levels
Discuss practical significance vs statistical significance
Identify potential confounders and how to address them

Key Topics to Cover

Confidence intervals and significance levels

Bayesian vs frequentist inference

Multiple testing correction (Bonferroni, FDR)

Power analysis and sample size calculation

Conditional probability and Bayes theorem

Regression analysis

How to Approach This

Define your hypotheses (H0 and H1) clearly before performing any test.
Calculate required sample size BEFORE running an experiment, using power analysis.
Remember the Central Limit Theorem: sample means become approximately normal with large n.
Watch for Simpson's paradox. Always segment data by key dimensions.
Distinguish between statistical significance and practical significance.

Possible Follow-up Questions

What assumptions does this test make, and how would you validate them?
How would you explain this result to a non-technical audience?
What alternative statistical method could you use here?
How would you handle multiple comparisons?

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Sample Answer

Problem Formulation

To analyze the 2% lift observed in the experiment, we will set up a hypothesis test. Let $H_0$ be the null hypothesis stating that there is no lift in the conversion rate (i.e., the conversion rat...

Solution Approach

Calculate sample proportions: Let $n_c$ and $n_t$ be the sample sizes for the control and treatment groups, respectively. The sample proportions are $\hat{p_c} = \frac{x_c}{n_c}$ an...

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