This short guide focuses on TikTok Statistics & Math interview questions and explains what makes them distinctive, what interviewers evaluate, what to expect, and how to prepare. TikTok tends to emphasize applied statistics tied to product metrics: A/B testing and experiment design, regression and causal reasoning, probability and sampling, variance and power, and practical diagnostics for data quality. Interviewers look for rigorous problem framing, correct use of statistical tools, clarity about assumptions, sensible tradeoffs, and the ability to translate numerical findings into product decisions. Coding fluency in SQL and Python for data wrangling is often assessed alongside statistical reasoning. For interview preparation, concentrate on core concepts (hypothesis testing, confidence intervals, power calculations, bias vs. variance, and common pitfalls), plus applied practice: design an experiment, diagnose a metric drop, and explain results to non‑technical stakeholders. Practice writing and speaking through short problem walkthroughs, rehearse common metric definitions (DAU, retention, CTR), and time-box technical drills in SQL/pandas. Mock interviews that combine stats with product sense and clear storytelling will best mirror what TikTok typically evaluates.