Statistics
Name: 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
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
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: http://www.experiment-resources.com/statiscal-analysis.html * Slaght, J.& Harben, P. (2009) Reading Course Book, Garnet: Reading p.43 * Slaght, J. , Harben, P. &Pallant, A. (2009) Reading and Writing Source Book, Garnet: Reading.pp.32-33