Data Science Quiz

Statistical analysis and modeling. The workflow that turns raw data into insight.

This category currently has 100 questions in the SERVBG quiz bank. Below are a few sample questions: the full interactive quiz shuffles through the whole set with instant scoring.

Sample questions

A two-sample t-test yields p=0.03 with significance level α=0.05. Which statement is correct?

We reject H0; the probability of observing a test statistic this extreme under H0 is 3%.
There is a 3% probability that H0 is true.
The effect size is large enough to be practically significant.
There is a 97% probability that H1 is true.
We accept H1 with 95% confidence because p < α.

In hypothesis testing, a Type II error (β) occurs when:

H0 is false but we fail to reject it.
The test statistic falls within the critical region under H0.
The confidence interval contains the null parameter value.
H0 is true but we reject it.
The p-value exceeds the significance level and H0 is true.

An A/B test is designed with 80% power to detect a minimum detectable effect of 2% lift. Halfway through, you see p=0.06 and stop early. The primary concern is:

Peeking inflates the Type I error rate beyond the nominal α.
The minimum detectable effect threshold must be recalculated after peeking.
Power calculations are irrelevant once data collection begins.
Stopping early always reduces variance and is statistically valid.
The test is underpowered because power was set at 80%.

You run 50 independent hypothesis tests at α=0.05. Using Bonferroni correction, the per-test threshold becomes:

0.0025
0.0005
0.01
0.001
0.05

The Benjamini-Hochberg (BH) procedure controls which error rate, and what does it guarantee?

Posterior error probability; the Bayesian probability of false discovery is ≤ q.
Per-comparison error rate; each individual test has Type I error ≤ q.
False discovery rate (FDR); the expected proportion of rejected H0s that are false positives is ≤ q.
Generalized error rate; the proportion of true nulls incorrectly rejected among all hypotheses is ≤ q.
Family-wise error rate (FWER); the probability of any false positive across all tests is ≤ q.

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