In this study, we proposed a method for correcting non-compliance of the web standard in webpages based on the characteristics of sampled webpages. We collected about 70,000 webpages by using a web crawler and analyzed them by applying various statistical methods. We found that the top three most frequent types of errors and warnings consist of about 60% and 80% of the total number of errors and warnings, respectively. Based on these results, we focus on correcting four most frequent errors and warnings, and showed that the strategy corrected about 95% of these errors and warnings. In addition, we found that different types of errors and warnings are correlated in such a way that correcting one type of error or warning influences on the correction of another types.