 The topic we are going to discuss today is data manipulation. This is very important to note that data manipulation could be discussed in two connotations. It could be discussed in positive connotations and as well as it could be talked about in a negative connotation. Today we are going to talk about data manipulation in a negative connotation. Data manipulation is a process in which scientific data is either forged, it presented in an unprofessional way, probably it is changed with this regard to the rules of academic world. So there could be the different variations which we can see that how data could be manipulated. But this is very much evident from these three definitions that data is not being manipulated in a positive manner. Why researches manipulate data? This is a question of a high interest that why there is need, even a certain need to manipulate the data. When we talk about students of psychology, we can understand that when they are doing any project which is for a brief term, they may be in a hurry to achieve data into a certain manner. Probably because of being less professional, probably being, you know, finding lack of time in their studies, they tend to go for data manipulation. Ideally, it happens in the mind that a hypothesis which is in their mind, the results of which are to be achieved, the trends of the data are likely to be seen. But when we talk about professional psychologists, professional researchers and mental health professionals, this is a very important debate to see that why researchers manipulate data. To avoid further experiment to solve data insecurities and inaccuracies to make the data process very easy, they generally do these kind of manipulation. When a specific kind of trends research is coming in which they are telling that these results, their final conclusion will not narrate our aims and our objectives in that way. As initially a researcher has done homework or planning on it, there generally as an unethical practice, professionals also manipulate data. Researchers may force the data, change some parameters without any experiment and further validation and present it in an unprofessional way. When we talk about type 1 error and type 2 error, they are probably the kind of the error which are being done by the researcher in a study. But when we talk about data manipulation, it is neither type 1 nor type 2, but still there are the errors in data which are being created by the researcher himself. So we need to understand that this is strictly an unprofessional and unethical activity. Data manipulation may result in distorted perception of a subject, which may lead to false theories of course, because when we present a result in an accurate way and it becomes a part of a record, it becomes a part of a data bank, then it may already challenge the theories produced earlier. Maybe it leads to a new theory, or it falsifies the available data sets. And this is one of the very important challenges which many other researchers faced that the base theories based on one research all of a sudden come and say that these research results are not validating the previous researches. Let me give you an example. If we talk about Adler's birth order theory and we see that it is a tried and tested theory. We apply it in the indigenous sample and the researcher manipulates the data in an unethical way. And he claims that this birth order theory does not pertain to the Pakistani indigenous population. That would be a very surprising and shocking result and that may probably going to challenge the whole theory. So this needs to be done in a very careful manner that the manipulation of any data will not only affect that research but it will also impact future researches in a very bad way. An experiment based on data that has been manipulated is risky and very unpredictable. Of course, when we talk about any data set which is being manipulated it becomes unpredictable and we cannot say that how many researches can be mislead by using that source. Now looking at two disadvantages of data manipulation. There could be the different ways we can see as disadvantages of data manipulation taking a close look into the issue. Disadvantages of data manipulation can be further divided into two ways. The first one is the disadvantages for author and researcher and the second one is disadvantages for the whole community. Now looking at the disadvantages of author and researcher. Primarily saying that most of the disadvantages are related to the defame and losing the credibility. Presenting questionable data and results can lead towards loss of reputation and trust in the field of research. When such a data set is presented, which is questionable, which is presented without validation it is meant to support a specific narrative. Whether it is a government narrative or a health department narrative. In the days of COVID, a researcher wants to give these findings and make his research very novel. He wants to publish it quickly. Because of COVID, mental health symptoms have been highly elevated and his percentage is nearly 80-90% of his research. The research will attract and publish a lot of data but a lot of questions will arise on his validity. Then putting himself or herself into the risk of getting banned by a scientific research organization. If one is being caught by doing data manipulation repeatedly it is difficult to regain his reputation and reputation. Then providing results that later will be proved wrong or dangerous can result of being arrested, jailed and punished in another way like getting banned, etc. Sometimes such research results have such strong implications and they are so unethical that punishments can be done on their basis. Then defaming and humility among rivals, colleagues and community of course those who are working with them in the Iraq can understand well that this data manipulation is happening and due to this, their community, colleagues and respect can also end. Then this advantage is for the community. This is on a researcher's stake that he will be defamed and his credentials will be questionable but his research is equally harmful for the community. Taking into consideration that our communities, people, government, companies, they listen to the experts like researcher, so giving them wrong results, concept thoughts and advice can be extremely dangerous and misleading. A lot of our research is basically used for policy making. It is used to support and strengthen different departments of the government. It is a food for thought for our different NGOs in which direction they should work. So if we mislead the community with our research then the results of the community will be very devastating. Then wrong concepts and results can either cause waste of time and resources or even threats people life. If you enter a scientific research, some wrong data is entered, manipulated and wrong results are taken out and you say this specific medicine can treat these three health elements and people start testing it on the basis of research then the loss of it can be a very large population. Similarly, the research for the formula Minks-Milks if the ingredients are not completely studied and cannot be validated or tested then the children's health can be in danger. Determination can prevent the growth of a community, country and results based on the false data can lead towards failure in real life practice. Of course, if the data would be false and the results would impact our community then the disaster situation can be created for a whole nation. So by saying this we need to understand that data manipulation is not a single task and it's not something which is related to one's own personal research but it has larger consequences which can even threaten the community and it can threaten the nations and many other people's life as well. Thank you for your time.