- 16.09.2019

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**Kezragore**

This situation is unusual; if you are in any doubt then use a two sided P value. But that does not prove the null hypothesis is true.

**Shakarg**

A crucial step in null hypothesis testing is finding the likelihood of the sample result if the null hypothesis were true. But it could also be that there is no difference between the means in the population and that the difference in the sample is just a matter of sampling error. This situation is unusual; if you are in any doubt then use a two sided P value. In these cases, the two considerations trade off against each other so that a weak result can be statistically significant if the sample is large enough and a strong relationship can be statistically significant even if the sample is small. P value tells you how rarely you would observe a difference as larger or larger than the one you observed if the null hypothesis were true. But it could also be that there is no relationship in the population and that the relationship in the sample is just a matter of sampling error.

**Maunos**

How likely is the effect observed in your sample data if the null hypothesis is true? In fact, it is extremely unlikely that the sample groups will ever exactly equal the null hypothesis value.

**Kazim**

How likely is the effect observed in your sample data if the null hypothesis is true? As an aid memoir: think that our cynical society rejects before it accepts. There is no relationship between the variables in the population. In fact, any statistical relationship in a sample can be interpreted in two ways: There is a relationship in the population, and the relationship in the sample reflects this.

**Branos**

The only situation in which you should use a one sided P value is when a large change in an unexpected direction would have absolutely no relevance to your study. High P values: your data are likely with a true null.

**Samuzil**

Everyone knows that you use P values to determine statistical significance in a hypothesis test. For example, when testing the null hypothesis that a distribution is normal with mean is less than or equal to zero against the alternative that the mean is greater than zero variance known , the null hypothesis does not specify the probability distribution of the appropriate test statistic. P value Probability of incorrectly rejecting a true null hypothesis 0.