 # P-VALUE

can some explain what a p value is with an example maybe? Thanks in advance

Here it is. Hope i make myself clear. Each statistical test has an associated null hypothesis, the p-value is the probability that your sample could have been drawn from the population being tested given the assumption that the null hypothesis is true. A p-value of .05, for example, indicates that you would have only a 5% chance of drawing the sample being tested if the null hypothesis was actually true. the p-value of a statistical significance test is basically the probability of obtaining values of the test statistic that are equal to or greater in magnitude than the observed test statistic.

The p value is the smallest level of significance for which the null hypothesis can be rejected. So basically the smaller the p value the more evidence you have to reject the null. In practice that means that if the p value is less than the level of significance we are testing for we reject the null. So if you are testing at the 95% significance level and the p value is 0,002 then you reject the null as the p value is smaller than 0,05. However if the p value is 0,06 then we do not reject the null hypothesis as it is larger than 0,05.

P-value in brief is the smallest level of significance for which the null hypothesis( being the hypothesis that researcher wants to reject) can be rejected. significance level is the probability that of making a type I error (alpha). synonimous with alpha ( signifiance level)

i think i kind of missed it

In raghuram’s answer, you need to put in some language like "indicates that you would have only a 5% chance of drawing a sample as contrary to the null hypothesis as that actually drawn if the null hypothesis was actually true. " I like ZXL’s which is less technical but the practical way to think about p-value.

i always thought the p stood for “probability”. I am correct?