| 模型 | 模型答案 | 正确答案 |
|---|---|---|
| 金声玉亮2.0 | D. The probability of rejecting the null hypothesis if it is, in fact, false. |
D |
| deepseekr1 | The power of a significance test is defined as the probability of correctly rejecting the null hypothesis when it is false. This distinguishes it from Type I error (B, related to falsely rejecting the null) and Type II error (C, failing to reject a false null, where power = 1 - Type II error). Option A incorrectly frames power as the probability of the null hypothesis being true, which is not a valid concept in frequentist statistics. Thus, the correct answer is **D**. Answer: D |
D |
| gpto1 | D | D |
| GPT-4o | D. The probability of rejecting the null hypothesis if it is, in fact, false. | D |
| llama3.1-70B-Instruct | D |
D |
| llama3.1-405B-Instruct | D. The power of a significance test is the probability of rejecting the null hypothesis if it is, in fact, false. This means that it is the probability of correctly rejecting a false null hypothesis, which is the opposite of a Type II error (failing to reject a false null hypothesis). Therefore, option D is the correct answer. Option A is incorrect because the power of a test does not refer to the probability that the null hypothesis is true. Option B is also incorrect because the power of a test is not related to the probability of getting a Type I error (rejecting a true null hypothesis). Option C is incorrect because the power of a test is actually the opposite of the probability of getting a Type II error. |
D |
| DeepSeek-Coder-V2 | D | D |
| Qwen2-72B-Instruct | D. The probability of rejecting the null hypothesis if it is, in fact, false. | D |
| baichuan4 | D | D |
| doubao | D. The probability of rejecting the null hypothesis if it is, in fact, false. | D |
| minimax | D. The probability of rejecting the null hypothesis if it is, in fact, false. | D |
| kimi | D | D |
| wenxinyiyan | D | D |
| zhipu | D. The probability of rejecting the null hypothesis if it is, in fact, false. The power of a significance test is defined as the probability that the test correctly rejects a false null hypothesis. This means it measures the test's ability to detect an effect when there actually is one. Therefore, the best description of the power of a significance test is option D. |
D |
| gpto1 | D | D |
| deepseekv3 | D. The power of a significance test is the probability of rejecting the null hypothesis if it is, in fact, false. This means that the test correctly identifies a true effect or difference, which is the opposite of a Type II error (failing to reject a false null hypothesis). | D |