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What does the researcher hope to do with null hypothesis the opposite of the research hypothesis?
Be able to reject the null hypothesis and accept the research hypothesis
What is power function in statistics?
In statistics, we have to test the hypothesis i.e., null hypothesis and alternative hypothesis. In testing, most of the time we reject the null hypothesis, then using this power function result, then tell what is the probability to reject null hypothesis...
Why is the level of significance always small?
The significance level is always small because significance levels tell you if you can reject the null-hypothesis or if you cannot reject the null-hypothesis in a hypothesis test. The thought behind this is that if your p-value, or the probability of getting a value at least as extreme as the one observed, is smaller than the significance level, then the null hypothesis can be rejected. If the significance level was larger, then statisticians would reject the accuracy of hypotheses without proper reason.
What is the major difference between the null and alternative hypothesis?
In research, a null hypothesis means that no results will be found. An alternative hypothesis means that results will be found.
Differences between null and alternative hypothesis?
The difference between the null hypothesis and the alternative hypothesis are on the sense of the tests. In statistical inference, the null hypothesis should be in a positive sense such in a sense, you are testing a hypothesis you are probably sure of. In other words, the null hypothesis must be the hypothesis you are almost sure of. Just an important note, that when you are doing a tests, you are testing if a certain event probably occurs at certain level of significance. The alternative hypothesis is the opposite one.
