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What assumption do we make in creating the randomisation distribution?
Construct a randomization distribution under the assumption that the null hypothesis is true. Use the randomization distribution to find the p-value. Decide if you should reject or fail to reject the null hypothesis. State a real-world conclusion in relation to the original research question.
Are randomization tests Parametric?
Randomization tests differ from parametric tests in almost every respect. There is no requirement that we have random samples from one or more populations—in fact we usually have not sampled randomly. Randomization tests don’t estimate parameters.
Why do independent samples t test not assume equal variances?
Note that this form of the independent samples t test statistic does not assume equal variances. This is why both the denominator of the test statistic and the degrees of freedom of the critical value of t are different than the equal variances form of the test statistic.
How to test with two independent samples, continuous outcome?
In the two independent samples application with a continuous outcome, the parameter of interest in the test of hypothesis is the difference in population means, μ 1 -μ 2. The null hypothesis is always that there is no difference between groups with respect to means, i.e., The null hypothesis can also be written as follows: H 0: μ 1 = μ 2.
How is the difference between two groups measured?
Here we compare means between groups, but rather than generating an estimate of the difference, we will test whether the observed difference (increase, decrease or difference) is statistically significant or not.
Is it reasonable to assume variability in comparison populations?
For analysis, we have samples from each of the comparison populations. If the sample variances are similar, then the assumption about variability in the populations is probably reasonable.