Data is the epicenter around which all research studies revolve, from health surveys to the number of users of a particular technology. People believe in facts and polls that depend on data. Researchers work to collect data, examine and interpret information. The primary duty of every researcher is to protect the integrity of data. Discussed here is a well-reported Dr. Poehlman case of scientific misconduct that made headlines in 2000. Dr. Eric Poehlman, of the University of Vermont, a well-known researcher in the field of aging and obesity, is now known for violation of ethics. Eric Poehlman, the obesity investigator, has conducted numerous studies and shown the world how obesity and aging are related. In particular, how menopause, aging and obesity are interconnected. The world believed the great obesity expert until the issue of research misconduct arose. In Eric's case, it was found that he handled the study data by himself and fabricated few data and then falsified some of it and collected funding from different organizations like National Institute of Aging and National Institute of Health. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay Lab technician DeNino had guessed that the data in the spreadsheet had been manipulated. Falsifying misleading data to obtain larger grants. His study on aging tends to show a tendency to get grants from the NIH. Dr. Poehlman has conducted various research activities. His study of Alzheimer's disease and its metabolism, the study of menopause on all 35 women. The study should have reported the facts of the real case and if the results are not as desired it could be due to the smaller number of subjects taken into consideration for the study. But neither of these things was done. It is bad practice to fabricate and falsify data. The effect of such a study is a disaster as this has led to misinterpretation of the data. Longitudinal Study of Aging: The study of aging where it all began. The individuals' data were manipulated to match the hypothesis. The lab technician working on a similar project couldn't understand how the data had delivered the expected statistical results overnight. The Menopause Longitudinal Study: The study was designed to analyze the effect of menopause on metabolic activities. The woman before and after menopause was examined twice over a six-year period. The hypothesis was that the metabolic changes were related to menopause rather than aging. Based on the evidence, it turned out that this longitudinal study was not conducted but only a falsification of data of 3 out of 35 women. This bogus study was proposed to acquire NIH grants and was reported in many journals and scientific articles. Alzheimer's Disease: The study of Alzheimer's disease is another example of data fabrication and falsification. The goal of this study to analyze changes in Alzheimer's disease in age-matched control subjects was misleading. According to the inspection, the initial statistics of subjects such as age, height were modeled from the original. Furthermore, the number of subjects was doubled by fabricating data to prove the established hypothesis. There may be many reasons, but a clear one is that the data should have been produced with actuarial results. Furthermore, data fabrication is unethical. This is manufacturing misconduct, data falsification. To reduce such misconduct. ”