Rejection of True Null Hypothesis is known as:-
**Core Concept**
The true null hypothesis is a statement that there is no significant difference or relationship between variables in a research study. Rejecting the true null hypothesis implies that there is a statistically significant difference or relationship between the variables.
**Why the Correct Answer is Right**
Rejecting the true null hypothesis is a crucial step in statistical analysis, allowing researchers to conclude that their findings are unlikely due to chance. This is achieved through hypothesis testing, where the null hypothesis is tested against an alternative hypothesis. If the p-value (probability of observing the results by chance) is below a certain significance level (usually 0.05), the null hypothesis is rejected. This rejection indicates that the observed results are statistically significant and unlikely due to random chance.
**Why Each Wrong Option is Incorrect**
**Option A:** Not applicable (this option is blank).
**Option B:** Type I error (this option is incorrect because a Type I error occurs when a true null hypothesis is rejected, but we are actually looking for the scenario where the true null hypothesis is rejected).
**Option C:** Type II error (this option is incorrect because a Type II error occurs when a false null hypothesis is not rejected, but we are actually looking for the scenario where the true null hypothesis is rejected).
**Clinical Pearl / High-Yield Fact**
It's essential to remember that rejecting the null hypothesis does not necessarily imply causation between variables. It only indicates that there is a statistically significant association, which may or may not be due to a causal relationship.
**Correct Answer: C. Rejection of the null hypothesis does not necessarily imply causation between variables.