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The null hypothesis for an anova states that?
The null hypothesis for a 1-way ANOVA is that the means of each subset of data are the same.
What is the meaning of null hypothesis?
In statistics, a null hypothesis is the hypothesis which you wish to test against some alternative. Often, it is framed in a way that is the opposite of what you wish to prove. You then collect the data and, if the resulting test statistic is such that observations which are at least as extreme as the one realised is very unlikely under the null hypothesis, then it is rejected and the alternative accepted.
What causes hypothesis to be rejected?
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.
When should you accept a null hypothesis?
The null hypothesis cannot be accepted. Statistical tests only check whether differences in means are probably due to chance differences in sampling (the reason variance is so important). So if the p-value obtained by the data is larger than the significance level against which you are testing, we only fail to reject the null. If the p-value is lower than the significance level, the null hypothesis is rejected in favor of the alternative hypothesis.
If we reject the null hypothesis what can we conclude about the alpha risk?
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.
What should you do if your data doesnt support your hypothesis?
Reevaluate your hypothesis, or reject the hypothesis. You should also recheck your data.
What do scientist do when their data does not support their hypothesis?
Discard or change the hypothesis.
Did your data support your hypothesis?
so you have to put in did it help you explain your hypothesis
What happens when the data doesn't support the hypothesis?
Change or abandon your hypothesis.
What should you do when your data will not support your hypothesis?
come up with new hypothesis
What happens if our data does not support our hypothesis?
If your data does not support your hypothesis, it means that there is not enough evidence to conclude that your hypothesis is true. In such cases, you may need to reconsider your hypothesis, collect additional data, or revise your experimental approach. It is important to acknowledge and learn from results that do not support your initial hypothesis in order to refine your research and understanding.
Does the data support the hypothesis?
You would need to tell us about the data, the hypothesis and so on for us to be able to answer.
What is learned if the data from an experience do not support the hypothesis?
some information; the data still provide valuable information about the hypothesis
What is learned if the data from an experiment do not support the. Hypothesis?
some information; the data still provide valuable information about the hypothesis
What is the of a conclusion?
to explain why the data support or reject the hypothesis
If the data doesn't support your hypothesis what should you do?
Regroup and propose another theory Propose another hypothesis
If your experiment does not support your hypothesis you should change your data to give support to the hypothesis. true or false?
False- The hypothesis is your prediction of what you expect to happen. If the data does not agree with your hypothesis you simply explain why your hypothesis did not come true and possibly investigate variable which would allow your hypothesis to come true.
