What does the p-value tell you? In statistics, the p-value is **the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test**, assuming that the null hypothesis is correct. A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.

## What does p-value of .9 mean?

That's pretty tiny. On the other hand, a large p-value of . 9(90%) means your **results have a 90% probability of being completely random and not due to anything in your experiment**. Therefore, the smaller the p-value, the more important (“significant“) your results.

## Is AP value of 0.04 Significant?

The Chi-square test that you apply yields a P value of 0.04, a value that is less than 0.05. The interpretation is wrong because a P value, even one that is statistically significant, **does not determine truth**.

## Is higher p-value better?

The smaller the p-value, the stronger the evidence that you should reject the null hypothesis. A p-value less than 0.05 (typically ≤ 0.05) is statistically significant. A p-value higher than 0.05 **(> 0.05) is not statistically significant** and indicates strong evidence for the null hypothesis.

## What does it mean when p is zero?

If the P=0, subtract that from 100% and you are **100% confident** that there is a statistical significance in the data you tested. Rejecting the NULL (that there is no difference) and ACCEPTING the alternative (that there is a difference) P=0.05, then you are 95% confident that the data is statistical.

## Related advise for What Does The P-value Tell You?

### Is Chi square significant?

If your chi-square calculated value is greater than the chi-square critical value, then you reject your null hypothesis. If your chi-square calculated value is less than the chi-square critical value, then you "fail to reject" your null hypothesis.

### What level of significance should I use?

The level of significance is a key input into hypothesis testing. It is the probability of rejecting the true null hypothesis, representing the degree of risk that the researcher is willing to take for Type I error. It is a convention to set the level at 0.05, while 0.01 and 0.10 levels are also widely used.

### What is the most commonly used significance level?

The significance level is typically set equal to such values as 0.10, 0.05, and 0.01. The 5 percent level of significance, that is, , has become the most common in practice.

### Is p-value of 0.10 good?

I.e. The result does NOT harbour anything biologically meaningful, it simply occurs by 'luck'. In other words a p-value of 0.10 means that if you are 'lucky' and 'hit' the one in ten times a significant result occurs by pure chance

### What does p-value not tell us?

A P-value is not the probability that the alternative hypothesis is false, or the probability that the null hypothesis is true, or the probability that the experimental data could have arisen by chance!