ENG Roath CHHORDA Level: EAP5 “ Statistics should be interpreted with caution as they can be misleading; they can both lie and tell the truth” Statistics are being used everyday to describe things in working and studying areas to show the productivity of the results they are hoping for. Therefore, people observe and notice alternative objects the world around. Throughout this fact, similarities and differences are such features that could endanger or turned out as advantages. This is called statistics.
Explanations of the word “statistics” are “ information based on a study of the number of times something happens or is present or other numerical facts” (Cambridge Advanced Learner’s Dictionary, 3rd Edition).
Definitely, observations and comparisons are both important processes to examine misleading statistics. This approach presented by learning from connections and experiences to analyze cautiously from unidentified, new things. This essay will first demonstrate type of misleading statistics including with some examples, and then reliable statistics will be examined by looking at some examples.
In the final part, some main points that evaluate good examples of statistics will be explored. “When statistics are extremely valuable, they are also notorious for being a means that people use to make false and misleading arguments” (Robert Korn, August 2012). For the probability of statistics, there will be no a hundred percent certainties for making sure it is definitely correct with no mistakes. Statistics give a way to look at the big picture and get a much more accurate way of understanding what is going on in the world than what people can get from individual observations.
Statistics can be used, intentionally or unintentionally to reach faulty conclusions. Misleading information is unfortunately the norm in advertising. “Data dredging is another huge problem especially in the Internet era where numbers and data are so easy to come by”(Siddharth Kalla (2011). Furthermore, survey questions are another most preferred area that can very easily be manipulated. Most often, statistics are obtained by taking a sample from a larger group and assuming the whole group has the same characteristics as the sample.
More than this, statistics are usually in the form of ranking, since it is surprisingly based on comparisons with other quantities rather than specifying specific amounts, there are special problems, which are need to be aware of. Part of the problem with ranking is that it does not tell much about the actual amount involved, which can easily to get confused. Here are some examples of misleading statistics, which are having more pictures than it actually has: Author: Lori Alden Audience: High school and college economics students
Summary: With this series of 12 puzzles, you can help your students become more discriminating consumers of economic statistics. Procedure: Each of the following problems shows one or more misleading statistics. See if your students can figure out why they’re misleading. 1. The following statistics suggest that 16-year-olds are safer drivers than people in their twenties, and that octogenarians are very safe. Is this true? As the following graph shows, the reason 16 year old and octogenarians appear to be save drivers is that they don’t drive as nearly as much people in other age groups. . “The best public schools offer a more challenging curriculum than most private schools. ” Are public schools therefore better than private schools? The problem is that the statistics are comparing different categories therefore it caused a mistake comparing private schools to other public schools. There are too many different statistical situations to consider them all, so the responsibility will often have to analyze the situation happening in front in order to make good judgments. Knowledge of statistics therefore will help looking behind the numbers and knowing the truth of being misled to believe something that is not true” (Siddharth Kalla (2011). Problems happened, solutions are made, and this essay will afterwards determines some solutions to solve some obstacles in analyzing such statistics. First of all, one simple strategy is to temporarily ignore the statistic that other has presented and ask what statistics would actually wanted to be, in order to make judgments about the issue involved.
Secondly, unless, having good access to the data and know how it is obtained, always recognize that statistics can be misrepresented what is going on. For example, if the information is obtained from a group that has a strong political or philosophical agenda, it can almost take for granted that their statistics have been carefully chosen to promote their point of view. Last of all, nevertheless, recognizing that statistics people present in general are frequently flawed does not imply that it is possible to depend on anecdotes about individual cases or a few own experiences (Siddharth Kalla, 2011).
These are commonly to be a typical of what happens in the world at large. Instead, the responsibility of individual should be refrained from judgment until getting the result of more reliable information about what is really going on. To conclude, questioning and studying reports that contain numbers are valuable. Just by looking at an argument uses numbers, does not mean it is correct. “Let us not have mistaken thoughts caused by misleading statistics”- Mistakestistics (Dr. Mark Drum, 2012). A good example of how to eliminate bias is a particular poll, from which the questions are open-ended, and does not give any options for an answer. This method gives a full opportunity for answers. Throughout this method, people have the option of answering however they choose. Some questions lead people to answer one way or another” (Discreet Deceit, 2012). In conclusion, statistics can both lie and tell the truth so in order to avoid from mistakes, it is to cautiously analyzing and learning from experience to examine each once properly.
Using own experience and common sense to analyze are the two best ways to avoid being fooled by misleading statistics. Bibliography: * CAMBRIDGE Advanced Learner’s Dictionary. (3rd Edition) * Misleading statistics lead to mistaken things: http://enewscourier. com/opinion/x1663461942/Misleading-statistics-lead-to-mistaken-thinking * Rowntree,D. (1982). Statistics without tears: a primer for non-mathematicians * Siddharth Kalla (2011). Statiscal Analysis. Retrieved 16 Aug. 2012 from Experiment Resources:
Cite this Essay Statistics: Statiscal Analysis
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