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Statistical Fallacies

Statistics are convincing and this has led many people to believe that they can be accepted without question. However, this is a false notion as misuses are probably as common as valid uses of statistics. The figures provide only raw material for someone to reason from-they seldom. If ever, speak for them, i.e. they have to be interprets. The inter-predation if data is a very difficult task and requires a high degree or skill Care judgment and objectivity. In the absence of these, there is every likelihood of the data being misused to prove things that are not at all true. In fact experience shows that the largest number of mistakes is committed consciously or unconsciously while interpreting statistical data and vey offer facts and figures are presented in such a manner that they are misinterpreted by most of the readers.

It should be noted that the motive or inert of the misuse of statistics is not at issue: fallacies designed to mislead and those committed unintentionally will not be distinguished. The effect is the same in both the cases although, to be sure, in the first case there is abuse of statistics and in the second case only a misuse.

Statistical fallacies may arise in collection, presentation, analysis and interpretation of data. The following are some of the specific examples illustrating how statistics can be misinterpreted of how fallacies arise in using statistical data and statistical methods.

Some of its main topics are:

4. Failure to comprehend the total background of the data

It should be noted that the motive or inert of the misuse of statistics is not at issue: fallacies designed to mislead and those committed unintentionally will not be distinguished. The effect is the same in both the cases although, to be sure, in the first case there is abuse of statistics and in the second case only a misuse.

Statistical fallacies may arise in collection, presentation, analysis and interpretation of data. The following are some of the specific examples illustrating how statistics can be misinterpreted of how fallacies arise in using statistical data and statistical methods.

Some of its main topics are:

**1.**Introduction to statistical fallacies**2.**Technical errors**3.**Inconsistency in definitions4. Failure to comprehend the total background of the data

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