Type I Error: This is when we incorrectly reject a true null hypothesis. For example, in a court trial, convicting an innocent person would be a type I error.
P-value: The p-value measures the strength of evidence against the null hypothesis and helps determine if results are statistically significant. A low p-value indicates strong evidence against the null hypothesis.
Confidence Level: The confidence level represents how confident we can be that our interval estimate contains the true population parameter. For example, if we have a 95% confidence level, we can say with 95% confidence that our interval contains the true value.