CSSGB · Question #114
The probability of accepting the alternative hypothesis (H1) when the null hypothesis (Ho) is true.
The correct answer is B. Alpha Risk. Alpha Risk (Type I error) is the probability of rejecting a true null hypothesis - equivalently, accepting H1 when H0 is actually true. This is the "false positive" error, and its probability is denoted by α (the significance level you set before a test, e.g., 0.05). Why the dist
Question
The probability of accepting the alternative hypothesis (H1) when the null hypothesis (Ho) is true.
Options
- ABeta Risk
- BAlpha Risk
- CAttribute Data
- DRandom Experiment
How the community answered
(13 responses)- A8% (1)
- B92% (12)
Explanation
Alpha Risk (Type I error) is the probability of rejecting a true null hypothesis - equivalently, accepting H1 when H0 is actually true. This is the "false positive" error, and its probability is denoted by α (the significance level you set before a test, e.g., 0.05).
Why the distractors are wrong:
- A (Beta Risk) is the opposite mistake: failing to reject H0 when H1 is actually true (a false negative / Type II error).
- C (Attribute Data) is a data classification (discrete/categorical data like pass/fail counts) - entirely unrelated to hypothesis test errors.
- D (Random Experiment) describes any process with uncertain outcomes; it's not an error rate concept.
Memory tip: Think Alpha = False Alarm - you're sounding the alarm (rejecting H0) when nothing is actually wrong. Beta = Blind Miss - you miss the real effect that was there.
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