H0 is the null hypothesis and h1 is the alternative hypothesis
In research, a null hypothesis means that no results will be found. An alternative hypothesis means that results will be found.
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.
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.
This is used in statistic to know whether to accept or reject a null hypothesis or alternative hypothesis
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
In research, a null hypothesis means that no results will be found. An alternative hypothesis means that results will be found.
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.
When more than one hypothesis is shown on a scientific paper, the alternative hypotheses can be numbered. They could use a format like, Hypothesis No. 1, Hypothesis No. 2, and so on.
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.
We have two types of hypothesis i.e., Null Hypothesis and Alternative Hypothesis. we take null hypothesis as the same statement given in the problem. Alternative hypothesis is the statement that is complementary to null hypothesis. When our calculated value is less than the tabulated value, we accept null hypothesis otherwise we reject null hypothesis.
The trick of course is to find an alternative a priori hypothesis.
Not sure about an interactive hypothesis: are you sure you don't mean alternative hypothesis?
It tells us that H1,H0 (alternative )hypothesis is selected
Either H1 or Ha.