What is the standard rejection rule?
The general rule of thumb is that if the value of test statics is greater than the critical value then the null hypothesis is rejected in the favor of the alternate hypothesis. In contrast to this, if the value of test statistics is less than the value of critical value then the null hypothesis is accepted.
When the p-value is less than or equal to the designated level of 0.05 the result is called a?
When the p-value is less than or equal to the designated level of 0.05, the result is called a A. statistically significant result. If the result of a hypothesis test for a proportion is statistically significant, then A. the null hypothesis is rejected.
How do you identify the appropriate rejection region for a given level of significance?
Rejection Regions and Alpha Levels You, as a researcher, choose the alpha level you are willing to accept. For example, if you wanted to be 95% confident that your results are significant, you would choose a 5% alpha level (100% – 95%). That 5% level is the rejection region.
Is the power of test based on symmetric distribution?
“The test is based on signed-rank of observations that are drawn from a symmetric continuous distribution population with unknown median. When the assumption about symmetric distribution fails, it can affect the power of test.” However, the Wikipedia page says that symmetry is not an assumption of the test.
When does the assumption about symmetric distribution fail?
When the assumption about symmetric distribution fails, it can affect the power of test.” However, the Wikipedia page says that symmetry is not an assumption of the test. My question is, if my data are not symmetric can I still apply the test?
What are the two types of rejection errors?
Two kinds of errors: Type I error is the error made when the null hypothesis is rejected when in fact the null hypothesis is true. Alpha (α) is the probability of rejecting a true null hypothesis.
What does the center mean in an asymmetric distribution?
Note that in case of asymmetric distributions the definition of the “center” is ambiguous, it could refer to the median, the mean, or the mode, which will for asymmetric data normally differ from each other.