In statistics, understanding Type I and Type II errors is crucial for accurate data interpretation. Type I errors involve falsely rejecting a true hypothesis, while Type II errors occur when a false hypothesis is accepted. Khan Academy introduces these concepts, teaching how to identify and calculate the probability of such errors, essential for informed decision-making.