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To prove the hypothesis.

To disprove the hypothesis.

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Q: What are two possible outcomes to prove an experiments hypothesis?
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Continue Learning about Statistics

What if your hypothesis is correct?

Your hypothesis is supported by the data. You cannot prove a hypothesis because somebody may do some other experiments and disprove it eventually. You can only disprove a hypothesis or indicate that it is supported by the data.


Can research be undertaken without developing a hypothesis?

Yes, Research can be undertaken without framing a hypothesis. The justification is in case of explanatory research, where the aim of your research is not to prove or disprove something, but to undertake an in depth study and go on exploring the investigation !!!!


If you have 5 football matches with 3 outcomes win lose or draw how many different combinations are there?

3 + 3 + 3 + 3 + 3 = 15 total possible outcomes. You can 'prove' this by laying out a table of possibles where a user might tick the result of each game..... Match....1....2....3....4....5 Win......._...._...._...._...._ Lose......_...._...._...._...._ Draw....._...._...._...._...._


When should i reject a null hypothesis?

When we state that the data analysis suggests that we "Reject the null hypothesis" we are stating that the sample statistic is sufficiently different from our assumed value of the population that it is unlikely to be explained by chance. If we use for example, that under the null hypothesis that engineers make on the average $120,000 per year. If we consider that the test statistic (size n) is normally distributed, we can use a two-tail test with an level of significance "alpha" to identify the lower and upper rejection zones on the normal distributon. If the test statistic falls in the non-rejection zone, we state that the "null hypothesis is not rejected." There are many good websites on hypothesis testing. Wikipedia provides a good summary of controversy on hypothesis testing. I note that some of the controversy stems from the idea that hypothesis testing will prove or validate population parameters, which is really beyond the scope of hypothesis testing theory. http://en.wikipedia.org/wiki/Statistical_hypothesis_testing A second way to determine whether the null hypotheis is to calculate p-values. For this, please see: http://en.wikipedia.org/wiki/P-value


Does Correlation alone complicates causation?

does not prove