CompTIA Data+ (DA0-002)Data AnalysisEasy
A data scientist is preparing to conduct a hypothesis test to determine if a new website design leads to a statistically significant increase in conversion rates. Before collecting data, they need to establish the maximum acceptable probability of incorrectly rejecting a true null hypothesis. What statistical concept are they defining?
- AConfidence Interval
- BP-value
- CEffect Size
- DSignificance Level
Show answer & explanationAnswer & explanation
Correct answer: D. Significance Level
The significance level (alpha, α) is the predetermined threshold for rejecting the null hypothesis. It represents the maximum probability of making a Type I error (incorrectly rejecting a true null hypothesis).
Why the other options are wrong
- A. A confidence interval provides a range of plausible values for a population parameter.
- B. P-value is calculated after the experiment and compared to the significance level.
- C. Effect size quantifies the magnitude of the difference or relationship, not the error probability.
Significance Level (α)
The probability of rejecting the null hypothesis when it is actually true (Type I error). It is set by the researcher before hypothesis testing.
- Also known as alpha (α).
- Commonly set at 0.05 or 0.01.
- Determines the critical region for hypothesis tests.
Memory trick: Alpha sets the 'A'-cceptable error rate.