반응형 R71 (R) Two sample t-test (Student's t, Welch's t ) Two sample t-test is to test whether the two population means are equal or not. So the null hypothesis here is, H0: the means of two populations are equal (M(A) =M(B)). The alternative hypothesis here is, H1: the means of two populations are different (M(A) !=M(B)).The common assumption for the two tests is "the sampling distributions are normally distributed."That is, both groups have the norma.. 2020. 10. 27. (R) Permutation Test - Non parametric method Permutation Test is a non-parametric method. Even though Permutation Test and Bootstrap Test are both non-parametric method, they have a difference, which is 'replacement.'Bootstrap test is the test method accomplished by allowing 'with replacement,' and the Permutation test is the test 'without replacement.' The two-sample t-test starts from the assumption that the sampling distribution is norm.. 2020. 10. 24. (R) Two sample Bootstrap Method I explained why Bootstrap method is important and how to use it in previous post. The difference between the previous one and this post will be the number of samples we are interested in. We want to assume the relationship ,for example the difference between more than one populations, by using bootstrap method. Let's assume that we want to show that weights of male and women are 0, that is weigh.. 2020. 10. 23. (R) One-sample Bootstrap Method Let's assume that we wanna get information of Weights of 20-30 Women worldwide. However there are about the 3 billion number of women. We cannot survey every woman in the world in the reason of time and cost limit.So we assume that we have surveyed on only 30 women's weight. It seems nonsense predicting trends of 3 billion population with only 30 samples. However, surprisingly, by using Bootstra.. 2020. 10. 17. 이전 1 ··· 3 4 5 6 7 8 9 ··· 18 다음 반응형
