**Type I Error (False Positive):** - This error occurs when…

**Type I Error (False Positive):**
- This error occurs when the null hypothesis is true, but we incorrectly reject it.
- It is also known as a "false positive" because we think we have found evidence of an effect when in reality, there is none.
- The probability of making a Type I error is denoted by the significance level \(\alpha\), often set at 0.05 (5%).
- **Example:** Suppose a pharmaceutical company is testing a new drug. The null hypothesis (\(H_0\)) is that the drug has no effect. A Type I error would occur if the test results lead us to conclude mistakenly that the drug is effective when it is not.