What type of flaw involves misinterpreting statistical data?

The flaw that involves misinterpreting statistical data is best identified as the fallacy of misleading statistics. This type of flaw occurs when data is presented or interpreted in a way that leads to a deceptive or inaccurate conclusion. Often, misleading statistics might involve cherry-picking data, presenting percentages without context, or using improper averages, all of which can distort the truth and mislead the audience.

On the other hand, a hasty generalization refers to drawing a broad conclusion based on insufficient evidence. While it may involve statistics, it doesn't specifically address the misinterpretation of statistical data itself.

Understanding this difference highlights why the fallacy of misleading statistics is the correct choice, as it directly pertains to the improper use or interpretation of statistical information rather than making a broad generalization from limited data.