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Managerial Roles

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Misuse of Statistics Studying about misuses of statistics with example:
Statistics:
Statistics is an aggregate of facts. Individual facts do not constitute statistics.The height of an individual does not constitute statistics. But the heights of 50 students in a class constitute statistics, since they are affected by multiplicity of causes, like age, heritage etc.The facts must be related to some department of enquiry. Collection of facts will not form statistics unless they are subjected to enquiry.Statistical data should be collected in a systematic manner keeping the purpose in view.
Statistics means the methods used for collection, classification, analysis and interpretation of numerical data. Statistics is also defined as the science which deals with collection, analysis and interpretation of numerical data.
 Limitations and Misuses of Statistics with Examples:
Statistics can be used only to study numerically valued data.
Statistics deals only with aggregate and not with individuals.
Statistical data are true only on an average.
Statistical data collected for given purpose cannot be applied to any situation.
It is not always possible to compare statistical data, unless they are homogeneous in character.
 Misuses of Statistics with Examples:
Statistical methods should be intelligently and carefully used as their misuses may lead to unsatisfactory results and dangerous conclusions. False conclusions will follow if the data collected is incomplete and unreliable. Also, if the data falls in the hands of untrained persons it is liable to be misinterpreted. Some of the famous sayings in this regard are "Statistical methods are the most dangerous tools in the hands of inexperts"; statistics are like clay of which we can make a good or evil as one pleases". Statistics has been misquoted in some places and this has earned a discredit to statistics. In such case the science of statistics is not to be blamed, but only those misrepresenting it have to be blamed.
Statistics has been misused and misinterpreted by inexperts and thus result the following sayings on statistics.
• "Statistics can prove anything".
• "Figures do not lie, liars figure".
• There are three kinds of lies-"lies, damned lies and statistics". What all these mean is that if the data are handles by untrained people then the results arrived from the statistical methods would be false.

 Misuse of statistics .
Occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.
The false statistics trap can be quite damaging to the quest for knowledge. For example, in medical science, correcting a falsehood may take decades and cost lives.
Misuses can be easy to fall into. Professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. Scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests.

Name 3 examples of abuse/misuse of statistics with regards to the correlation vs. cause & effect relationship.?
These examples can be from your work place, politics or other sources

The military statistic that more people die of on work accidents then in the military in a time of war is a misused as propaganda. They are using the deaths, form all work accidents, rather than just the same ratio (1 average worker, to 1 marine.)

Another is: High housing costs are only part of the reason young adults are staying home in greater numbers than ever before.
Since 1970, the percentage of people ages 18 to 34 who live at home with their family increased 48%, from 12.5 million to 18.6 million, the Census Bureau says. with some research, i found it to be totally faulty.

How does the media misuse statistics?
I needed examples on the misuse of statistics in the media. Whether it be relating to health, war, or things about teenagers that create stereotypes.

to add to the above answer - yeah, and they say things like, example "a whopping FIFTEEN PERCENT of heart failure patients are smokers!" to give the impression smoking gives greater risk of heart failure, when really, eighty five percent of people who've had heart failure didn't/don't smoke....
OR they can say it like "85 of every 100 heart failure patients were not smokers" which twists it to give the meaning that smoking gives you less risk of heart failure when in reality, it may not even be a factors

Types of misuse
 Discarding unfavorable data
 Loaded questions
 Overgeneralization
 Biased samples
 Misreporting or misunderstanding of estimated error
 False causality
 Proof of the null hypothesis
 Data dredging
 Data manipulation
 Other fallacies

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