Probability of Null Hypothesis being true
If p is less than a threshold , reject Null Hypothesis
The p-value represents the probability of obtaining Test statistic at least as extreme as the observed results, assuming that the null hypothesis is true.
Key Concepts
- Test Statistics and Null Hypothesis
- Most test statistics are calculated under the assumption of a null hypothesis
- For example, when comparing two sample means, we assume both samples come from the same population
- Statistical Significance
- Commonly uses a 5% threshold - if p-value < 0.05, we consider the difference significant
- Tests whether the differences between sample groups are statistically meaningful
Important Considerations
The p-value incorporates both effect size and sample size (n) information. This means that even samples from the same population might show p-values below 0.05 due to large sample sizes. Therefore, it's crucial not to rely solely on p-values for decision-making.
P-values are specifically related to the T test and help determine the statistical significance of observed differences between groups.
