Statistical errors occur when the results of a study or analysis do not accurately reflect the true situation. These errors can arise from various sources, including sampling mistakes, measurement inaccuracies, or biases in data collection. Understanding these errors is crucial for interpreting data correctly and making informed decisions. There are two main types of statistical errors: Type I error and Type II error. A Type I error happens when a true null hypothesis is incorrectly rejected, while a Type II error occurs when a false null hypothesis is not rejected. Both types can lead to misleading conclusions in research and analysis.