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.
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The null hypothesis expresses the likelihood that the event will NOT occur or be significant, while the alternative hypothesis states the likelihood that it will.
In research, a null hypothesis means that no results will be found. An alternative hypothesis means that results will be found.
with the alternative hypothesis the reasearcher is predicting
H0 is the null hypothesis and h1 is the alternative hypothesis
The null hypothesis is that there is no change in the population mean while the alternative hypothesis is that there is a change in the mean. The null hypothesis is stated as Ho:Mu=? in statistics while the alternative hypothesis is stated as Ho:Mu(<,>,≠)? depending on whether you are looking for mu to be greater, less than, or not equal to population mean.
Yes; the null hypothesis, H0, always includes an equality. The alternative hypothesis, H1, is >, <, or does not equal.