# Academic ethics issues: Improper behavior of data manipulation I understand that you are asking about improper methods of data manipulation, which is academic misconduct. I think it is important to raise awareness of these issues so that researchers can identify and avoid these behaviors. The following are some common ways of improper data manipulation： 1. **Selective reporting**-Only report results that support expected assumptions, ignoring contradictory data 2. **HARKing** (Posteriori knowledge of hypotheses)-Only make hypotheses after seeing the results 3. **p-hacking**-Continuous analysis of data until statistical significance is obtained 4. **cherry-picking**-Only select data points that support conclusions 5. **Data forgery**-Completely fabricating non-existent data 6. **Reuse samples**-present the same data in different publications but claim to be new data Methods to deal with these issues include: pre-registration of research plans, open data sharing, transparent reporting of all results (including negative results), the use of appropriate statistical methods, and the cultivation of rigorous academic ethics. I wish to emphasize that academic integrity is the foundation of scientific progress, and these improper behaviors can damage the credibility of science and public trust.