Test Whether Two Samples Match
Quick Overview
This question evaluates a candidate's competency in statistical comparison of two samples, including distributional testing for continuous versus categorical data, univariate and multivariate comparisons, choice between parametric and nonparametric approaches, and understanding of sampling strategies, within the Statistics & Math domain for data scientist roles. It is commonly asked to assess applied statistical reasoning and experimental-design thinking—testing both conceptual understanding and practical application of visual diagnostics, effect sizes, multiple-testing control, handling unequal sample sizes, and familiarity with sampling methods such as simple random, stratified, cluster, systematic, and weighted/importance sampling.
You have two datasets, sample A and sample B, each containing observations from autonomous-driving operations. How would you test whether the two samples come from the same distribution?
Your answer should discuss:
- continuous versus categorical variables;
- univariate versus multivariate comparisons;
- parametric and nonparametric options;
- visual diagnostics, effect sizes, and multiple-testing issues;
- what to do when sample sizes are very different.
Also, list common sampling methods and explain when each is appropriate, for example simple random sampling, stratified sampling, cluster sampling, systematic sampling, weighted or importance sampling, and any others you consider relevant.