The null hypothesis for a 1-way ANOVA is that the means of each subset of data are the same.
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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.
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.
If we reject the null hypothesis, we conclude that the alternative hypothesis which is the alpha risk is true. The null hypothesis is used in statistics.
you do not need to reject a null hypothesis. If you don not that means "we retain the null hypothesis." we retain the null hypothesis when the p-value is large but you have to compare the p-values with alpha levels of .01,.1, and .05 (most common alpha levels). If p-value is above alpha levels then we fail to reject the null hypothesis. retaining the null hypothesis means that we have evidence that something is going to occur (depending on the question)
The null hypothesis will not reject - it is a hypothesis and is not capable of rejecting anything. The critical region consists of the values of the test statistic where YOU will reject the null hypothesis in favour of the expressed alternative hypothesis.