Your assignment is to prepare and submit a paper on consumer mathmatics and statistics. That is a faulty connection. Noticeably, the use of the word “might” reduces the ability of the claim to be 100% true. For we know, using words such as “may” or “might”, does not guarantee or assure us that a result will always follow. The researcher has not established a correction connection, thus, used the statistics incorrectly, specifically implied connection mistake was committed (Statistics, nd). To address the problem, the researcher must avoid using words that would suggest a doubt to the readers.
Another misuse of statistics is called suspect samples. To illustrate this, let us consider a statement made by an author in a recent article, claiming that 71% of adults do not use sunscreen. Determining the correct sample size and correct sampling method is one of the crucial parts of doing statistics. The previous statement is quite misleading since the sample used was not declared or where did the sample has came from was not stated. If this 71% of the adults are from the North Pole, which there is no enough sunlight for nearly four months, then that would be true. However, the conclusion would not be correct since those adults do not represent the whole number of adults in the US or in the world. Or, if the samples were from countries like Saudi Arabia, the Middle East, or regions experiencing a hot climate and direct sunlight, the results would have been different. That is, we can conclude that most adults are using sunscreen. In eliminating the mistake, the researcher should present a data or report that the readers can conclude that the samples are really representative of the population being studied, or indicate a reliable source of the information (Chu-Carroll, 2007).
In the two previous examples, implied connections and suspect samples were made (Misuses of Statistics, 2011). We have also seen that the improper use of statistics would lead to erroneous conclusions. Any imprecise connections and inaccurate data sampling or samples should be minimized or in all cases should be resolved. Particularly, in the field of medicine, drugs being sold in the market must have been thoroughly tested, and proper documentation must have been done for much of at issue are the lives of people. Hence, in doing interpretations of statistics, the researcher should not only consider the appropriateness of the interpretation to the readers but also intricately evaluating that no misuse of statistics was made (Chu-Caroll, 2007).