with the alternative hypothesis the reasearcher is predicting
Null hypothesis of a one-way ANOVA is that the means are equal. Alternate hypothesis a one-way ANOVA is that at least one of the means are different.
No.
Yes, usually.
research hypothosis
When writing hypotheses the null hypothesis is generally the hypothesis stating that there will be no significant difference between the variables you are testing. An alternate hypothesis would be a hypothesis suggesting that the results will be anything other than not significant. For example if you were testing three concentrations (low, medium, and high) of a type of medication on cancer cells, then one example of an alternate hypothesis would be that the medium concentration would decrease the number of viable cancer cells.
No, it never does!
A different claim proposing another hypothesis
You test a hypothesis after you form it. But lets go over the scientific method anyway. You start with a situation, then you come up with a question, then a hypothesis: there are two kinds of hypothesis, null and alternate, null means that the results dictate that the treatment shows no Significance, where alternate shows that the groups have difference, which is significance. You test the hypothesis in an experiment, and there are many different tests that you can apply to the DATA you collect.
The two main types of hypotheses are simple and complex hypothesis. The simple hypothesis predicts the relationship between a single dependent and independent variables. On the other hand, the complex hypothesis describes the relation between two or more dependent and independent variables.
The scientist could reevaluate the hypothesis, consider alternate explanations for the results, or modify the experimental design to address potential limitations. It is also important to replicate the study to confirm the findings and consult with colleagues for insights.
Whether your alternate hypothesis is directional (one-sided) or non-directional (two-sided) is largely up to you but must be determined before you conduct your experiment, not after. It's not defined by the outcome.
In statistics, a null hypothesis (H0) is a hypothesis set up to be nullified or refuted in order to support an alternative hypothesis. When used, the null hypothesis is presumed true until statistical evidence, in the form of a hypothesis test, indicates otherwise - that is, when the researcher has a certain degree of confidence, usually 95% to 99%, that the data does not support the null hypothesis. It is possible for an experiment to fail to reject the null hypothesis. It is also possible that both the null hypothesis and the alternate hypothesis are rejected if there are more than those two possibilities.