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October 16, 2015 12:48
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You compare the mean score of each group using a simple significance test, and you obtain p = 0.01, indicating there | |
is a statistically significant difference between means. | |
이 상황에서 다음의 질문에 대한 T/F 는 각각 무엇일까요? | |
1. You have absolutely disproved the null hypothesis ("There is no difference between means") | |
F: 귀무가설이 맞다고 가정했을 때 현재 observation보다 극단적인 값을 얻을 확률이 0.01이라고 알 뿐 절대적인 disprove는 불가능하다. 그냥 결정하기 나름? | |
2. There is a 1% probability that the null hypothesis is true | |
F: p-value means that probability of getting a extreme or more than extreme than what was observed given **that null hypothesis is true** | |
3. You have absolutely proved the alternative hypothesis ("There is a difference between means") | |
F: 1과 마찬가지로 absolutely prove란 없는 듯? | |
4. You can deduce the probability that the alternative hypothesis is true | |
F: **귀무가설이 참인 가정인 가정하에** 귀무가설을 기각했을 때 그 결과가 틀릴 확률을 알 뿐 대립가설이 참일 확률은 영원히 모른다. | |
5. You know, if you decide to reject the null hypothesis, the probability that you are making the wrong decision | |
T: p-value가 위 문장이랑 사실상 같아 보인다. | |
6. You have a reliable experimental finding, in the sense that if your experiment were repeated many times, you would | |
obtain a significant result in 99% of trials | |
?: significant result가 뭘까요. 일단 찍어보자면 T |
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