Statistics and Quant Research Cycle Review
Review the first statistics and quant research cycle: inference basics, hypothesis testing, sample size, bias, backtesting, and overfitting.
Candidates consolidating inference, bias, and backtesting basics.
Review inference basics
You should be able to explain sampling distributions, standard error, confidence intervals, p-values, and hypothesis tests without confusing their meanings.
Review research pitfalls
Selection bias, survivorship bias, lookahead bias, multiple testing, and overfitting are core risks in research-style prompts.
Concrete final drill
Take one toy strategy result and discuss p-value, sample size, multiple testing, leakage, survivorship, costs, and overfitting risk.
Choose next drills
If inference language is weak, drill hypothesis testing. If research caveats are weak, drill backtesting and bias prompts.
Common mistakes
Candidates often finish the cycle with formulas but no caveats. Quant research interviews expect both calculation and skepticism.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.