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1711Backtest Slide Misreads p = 0.03A PM deck says: ‘The event-study p-value is 0.03, so there is a 97% probability the signal is real.’ What is the statistical mistake?统计简单essay未尝试免费1712Statistical Significance Is Not Economic SignificanceWith millions of observations, a strategy's average edge is estimated at 0.2 basis points and is highly statistically significant. Why is 'highly significant' not enough to conclude the strategy matters economically?统计简单essay未尝试免费1713No Significance Is Not No EffectA small-cap execution pilot reports p = 0.18 and the note says ‘there is no effect, so we should stop the project.’ Why is that too strong?统计简单essay未尝试免费1714Optional Stopping as a p-Hacking MechanismA PM checks the p-value every hour and stops the experiment as soon as p < 0.05. Why does this inflate false positives?统计中等essay未尝试面试订阅1715The Prosecutor's Fallacy in a Trading ContextA rare anomaly occurs in only 1 out of 10,000 normal days. A model flags today's pattern as one that would happen with probability 1/10,000 under the null, and someone concludes the null must almost certainly be false. What key base-rate issue are they missing?统计中等essay未尝试面试订阅1716Replication Probability Is Not 1 - pA researcher says: ‘This alpha had p = 0.04, so replication next quarter is 96% likely.’ Why is that interpretation invalid?统计简单essay未尝试免费1717Significant but Commercially UncertainA venue-routing tweak delivers p = 0.01, but the 95% confidence interval for annual savings is [10k, 1.2m]. Why should the team still be cautious?统计简单essay未尝试免费1718Best-of-50 Reporting Without AdjustmentA researcher tests 50 candidate features and only reports the one with the smallest p-value, which happens to be 0.01. Why is it misleading to present 0.01 as if it came from a single pre-specified test?统计中等essay未尝试面试订阅17190.049 vs 0.051 Decision CliffTwo backtests differ only slightly: one reports p = 0.049 and the other p = 0.051. Why is it bad practice to call one ‘real’ and the other ‘not real’ purely because one is below 0.05?统计简单essay未尝试免费1720Low Prior Probability and Positive Predictive ValueSuppose only 1% of tested trading ideas are genuinely predictive. A testing pipeline has 80% power and a 5% false-positive rate. Conditional on obtaining a positive result, what fraction of positives are truly real?统计中等derivation未尝试面试订阅1721Switching to One-Sided After Seeing the SignA two-sided test is not significant, but the estimated coefficient has the expected sign. The analyst then reports the one-sided p-value instead. Why is that invalid if the direction was chosen after looking at the data?统计中等essay未尝试面试订阅1722Cherry-Picked EndpointA note tests 12 strategy diagnostics but highlights only the one with p = 0.02. What trap should the reviewer flag?统计简单essay未尝试免费1723Underpowered Winner’s CurseA sparse signal library was screened on short samples; the surviving signal is significant but came from a very low-power environment. Why should its in-sample effect size be viewed skeptically?统计中等essay未尝试面试订阅1724Conditioning Direction ErrorA reviewer writes: ‘p = 0.07 means the null hypothesis is true with probability 7%.’ What is wrong with the conditioning direction?统计简单essay未尝试免费1725Fail to Reject vs AcceptAn experiment does not reject the null at 5%. The team writes ‘the null is accepted.’ What is the correct correction?统计简单essay未尝试免费