Can you partially accept a hypothesis

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Create a free Team What is Teams? Learn more. Can you accept the alternative hypothesis if the global test is significant but the pairwise comparisons are not? Ask Question. Asked 7 years, 9 months ago. Active 6 years, 1 month ago. Viewed 3k times. Improve this question. Parul Kathuria Parul Kathuria 31 1 1 silver badge 2 2 bronze badges.

I would not use the phrase " partially accepted". Add a comment. Active Oldest Votes. In that sense, the research hypothesis you stated is indicated. Edit: To address the specific phrasing of the research hypothesis being 'partially accepted' - It depends on what you mean by "correct".

I think the important thing is to convey exactly what null was rejected. Improve this answer. The paradox is that this particular study was itself funded by the gambling industry!

In social science, I think we should move away from the idea that we have hypotheses that are confirmed or not. My concern here is similar to my issues with null hypothesis statistics testing:. Conflation of rejection in a null hypothesis significance test with rejection of a substantive hypothesis. Rejection of null hypothesis A taken as support for, or confirmation of, favored alternative hypothesis B.

Dichotomization—or, one might say, premature dichotomization—throwing away information at all stages of a study, from design and data collection through coding and data analysis. The key point here is that the problems of null hypothesis significance testing arise not just with original studies but also with replications, meta-analyses, literature reviews, and the like.

That is, it assumes that whatever you are trying to prove did not happen hint: it usually states that something equals zero. For example, the two different teaching methods did not result in different exam performances i. Another example might be that there is no relationship between anxiety and athletic performance i. The alternative hypothesis states the opposite and is usually the hypothesis you are trying to prove e.

Initially, you can state these hypotheses in more general terms e. Depending on how you want to "summarize" the exam performances will determine how you might want to write a more specific null and alternative hypothesis. For example, you could compare the mean exam performance of each group i. This is what we will demonstrate here, but other options include comparing the distributions , medians , amongst other things.

As such, we can state:. Now that you have identified the null and alternative hypotheses, you need to find evidence and develop a strategy for declaring your "support" for either the null or alternative hypothesis.

We can do this using some statistical theory and some arbitrary cut-off points. Both these issues are dealt with next. The level of statistical significance is often expressed as the so-called p -value.

Depending on the statistical test you have chosen, you will calculate a probability i. Another way of phrasing this is to consider the probability that a difference in a mean score or other statistic could have arisen based on the assumption that there really is no difference. Let us consider this statement with respect to our example where we are interested in the difference in mean exam performance between two different teaching methods.

If there really is no difference between the two teaching methods in the population i. So, you might get a p -value such as 0. However, you want to know whether this is "statistically significant".

We reject it because at a significance level of 0. Whilst there is relatively little justification why a significance level of 0.

However, if you want to be particularly confident in your results, you can set a more stringent level of 0.