Statistical Analysis
P Value
Objective:
Introduction.
Definition of p value.
Calculation of p value.
Is p-value statistically significant.
Introduction:
There are two main types of inferential statistics, mainly, confidence interval, and hypothesis testing (p-value).
Definition:
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 hypothesis This indicates there is an association or a difference
Null hypothesis This indicates there is no association or no difference
Example:
a p value of 0.0254 is 2.54%.
On the other hand, a large p-value of .9 (90%)
The smaller the p-value, the more important (“significant“) your results.
How do you calculate the p-value?
P-values are usually automatically calculated by your statistical program or website (R, SPSS, Excel etc.).
Example using excel
How do you know if a p-value is statistically significant?
The level of statistical significance is often expressed as a p-value between 0 and 1.
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.