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  • - [Instructor] We're told a sociologist studying fertility

  • in Argentina and Bolivia wanted to test

  • if there was a difference in the average number

  • of babies women in each country have.

  • The sociologist obtained a random sample

  • of women from each country.

  • Here are the results of their test.

  • So they take a sample of 75 women in Argentina,

  • and these women had a mean of 2.4 babies each,

  • with a standard deviation of 1.5.

  • And then the standard error of the mean was 0.17.

  • And then they calculated similar statistics for Bolivia.

  • And then they give us the t test

  • for the means being different,

  • and we were able to calculate these statistics.

  • And they say assume that all conditions

  • for inference have been met.

  • At the alpha equals 0.05 level of significance,

  • is there sufficient evidence to conclude

  • that there is a difference in the average number

  • of babies women in each country have?

  • So pause this video, and see if you can answer that.

  • All right, now let's work through this together.

  • So this is classic hypothesis testing right over here,

  • where your null hypothesis is actually going to be

  • that your means are the same,

  • so that the mean in Argentina is equal

  • to the mean in Bolivia.

  • And then your alternative hypothesis is

  • that your means are different.

  • And what you do is you say, all right,

  • if we assume the null hypothesis, what is the probability

  • that we would have gotten means this far apart?

  • And that's what our p-value tells us,

  • that we have a 0.31 probability,

  • or a 31% probability, of getting means this far apart.

  • Now, if your probability, assuming the null hypothesis,

  • is below your level of significance,

  • your alpha right over here,

  • then you would say, all right,

  • that seems like such a low probability.

  • I'll reject the null hypothesis,

  • which suggests the alternative hypothesis.

  • But in this situation here,

  • if we compare our p to our alpha,

  • we see that our p-value is for sure greater than our alpha.

  • So in this situation,

  • I mean you could see it right over here,

  • 0.31 is for sure greater than 0.05.

  • So in this situation, we cannot reject the null hypothesis,

  • cannot reject

  • our null hypothesis.

  • And so there is not sufficient evidence

  • to conclude that there is a difference

  • in the average number of babies women in each country have.

- [Instructor] We're told a sociologist studying fertility

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用P值進行兩個樣本t檢驗的結論 (Conclusion for a two sample t test using a P value)

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    林宜悉 發佈於 2021 年 01 月 14 日
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