Statistical significance: Statistical significance indicates whether an observed effect or relationship in data is unlikely to have occurred by chance alone.
Practical significance: Practical significance refers to the importance or relevance of a statistically significant result in practical terms. It considers factors such as effect size, cost-benefit analysis, and real-world implications.
Type I error: Type I error occurs when we reject a true null hypothesis (e.g., there is no difference) in favor of an alternative hypothesis (e.g., there is a difference) based on our statistical analysis.