Question: 1- Inaccuracies or misrepresentation of data can occur both purposely. Sometimes poor sampling methods or other sources of injustice influence the accuracy of the data without the researcher realizing there is a problem, these could be caused by a lot of factors such as; insufficient or deceiving data, misleading visualization of the result and insufficient reasoning on the basis of results (Smith, 2015). A simple example, which occurs very frequently, is the presentation and clarification of data where some data items are absent. A much-reported example of this concerned the analysis of the failure of O -rings on the US space shuttle in 1986. NASA staff and their contractors examined the pattern of failures of O-rings during starts against temperature. They concluded that the data showed no apparent relationship between the number of failures and temperature.

2- Most of our politician's abuse numbers exploit them and misinterpret them for their gain. All politicians love to quote numbers and say, look what I have done but are those numbers accurate. When they share what they have done for example creating so many new job but how many jobs were lost. They never reveal the negative side or never include all the variables when presenting their numbers .I hope America has realized that politicians will say and do anything to win.

3- Statistics is a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting, and drawing conclusions based on the data (Jones, 2016). Using statistics and graphs can be misrepresented in many ways that can be either accidental or intentional.

Data can be ill judged if the sampling is not done appropriately. A random selection without background knowledge or without specified criteria leads to misunderstanding of the data. Another reason of misunderstanding is difference in causation and connection. Feature may co-exist though, may not be reliant on one another. One of the influenced areas in medical world is pharmaceuticals. Pharmaceutical companies use mistaken data in competitive markets. Generic medicines for same purposes are branded out and to advertise a misguiding catalog is used. The most essential thing to consider while comprehending or predicting a result of a statistical analysis is a well-balanced and well-selected population. Sample partakers should be chosen considering different aspects of the problem so that the result will not be unfair. This demands the proper understanding of the statistical tools and how to select the sample population. Furthermore, the sample size should be sufficiently large enough to get more fixed conclusions.