Statistics mock interviews for data science
Statistics questions sound simple (what does a p-value mean, how long should this test run), but they test whether you really understand the assumptions behind methods you use every day.
PrepLinx's AI interviewer asks statistics and experimentation questions out loud and follows up on your reasoning: why that test, what you're assuming, how you'd explain the result to a product manager. A code editor and whiteboard are there for calculations.
What this round tests
Hypothesis testing
Choosing an appropriate test and interpreting it correctly.
Probability
Distributions and probability reasoning, including the classic puzzles.
Experiment design
A/B test setup, sample size, duration and common pitfalls.
Inference
Confidence intervals, and what they do and don't mean.
Regression
Fitting, interpreting and diagnosing regression models.
Communication
Explaining statistical results to people who aren't statisticians.
Practice questions
Examples of the questions and follow-ups you can expect. Practice saying your answers out loud, not just reading them.
- What does a 95% confidence interval actually mean?
- You ran 20 A/B tests and one was significant at p < 0.05. What do you conclude?
- How would you choose the sample size for an experiment?
- A coin lands heads 60 times in 100 flips. Is it biased?
- When is the median a better summary than the mean?
- How do you interpret a regression coefficient when your features are correlated?
How a PrepLinx session works
- 1
Choose the round
Pick the role, the interview type and a difficulty (easy, medium or hard). Optionally add a job profile with your resume and the job description, so the questions relate to that job.
- 2
Interview out loud
The AI interviewer speaks, listens to your answers and asks follow-ups. It doesn't give hints or say whether you're right, just like the real thing. The session runs up to 30 minutes.
- 3
Get scored feedback
A report with a 0–10 score for each dimension the round is graded on, strengths quoted from your own words, weaknesses, concrete improvements and an overall hiring signal, plus the full transcript.
How to prepare
Define before you compute
State the null hypothesis, the metric and the assumptions before any calculation.
Watch for multiple comparisons
Peeking, many metrics and many variants all inflate false positives. Mention it before you're asked.
Interpret in plain language
Finish every answer with what the result means for the decision.
Know the classics
Bayes' theorem, the central limit theorem, type I and type II errors, and power come up constantly.
Frequently asked questions
Does this cover A/B testing?
Yes. Experiment design and A/B testing are core topics in the statistics round, along with hypothesis testing, probability, confidence intervals and regression.
Do I need to do calculations?
Sometimes. You can work them out loud, on the whiteboard, or in the code editor in Python or R.
Is it only for data scientists?
It's part of the data scientist track, but it's useful for anyone whose interviews include statistics or experimentation, such as product analysts.
How long is a session?
Up to 30 minutes.
Practice other rounds
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Practice your next statistics interview
4 full interviews free, with scored feedback. No credit card, and they don't expire.
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