There are too many ways to list, really, but here are a few common ones.
First, and probably most common, is to assume that a statistical relationship equals a cause and effect one. You can, for example, quite accurately predict the damage a fire will do by counting the number of firefighters who show up to put it out. But that does not mean that firefighters cause fire damage. Other examples of this abuse can be seen everywhere in advertising. Just because kids who eat a healthy breakfast do better in school, that does not mean that the breakfast caused it or that if you suddenly start eating better your grades will improve. More likely, parents who have the sense and caring to prepare a healthy breakfast caused the kids to do better in school.
Second, you can ignore other contributing variables. The classic example here is the fact that predominantly non-white neighborhoods have higher crime rates. For years, this statistic was touted as proof that non-whites are inherently violent and criminal-minded. Yet when you also consider the economics of a neighborhood, it turns out that poverty leads to higher crime, not skin color.
Lastly, and this one is thankfully rare but also the most devious, you can intentionally delete cases or otherwise manipulate data to achieve the results you want. (Despite claims to the contrary, this rarely happens in legitimate science).
But in general, a misuse of statistics has occurred any time that you rely too heavily on the numbers and forget that they are just numbers. If there is no practical connection between the numbers and what they represent, no common sense analysis of what the numbers mean and what could have been missed, then statistics is nothing more than just fancy math and fodder for sound bites on the evening news.
The two main branches of statistics is Descriptive statistics and inferential statistics.
father of statistics
two types is: 1. Descriptive statistics. 2. Inferential statistics.
limitations of statistics are as follows: 1. Statistics does not deal with an individual 2.It is not suitable to the study of qualitative phenomenon 3.Statistical relations are not exact 4.Statistics is liable to be misused 5.Statistics is only a means
Yes. All knowledge can be misused.
coal is being misused in many ways
Things like sky boxes are misused by leaving it on standby.
squatting is misused by the digging up of the earth and destroying plants and trees
if misused, you may get electric shock, you may get huge electricity bills
Despite The usefulness of statistics in Many fields, impression should not be carried that statistics are like magical devices which always provide the correct solution of problems.1. Statistics does not deal with isolated measurement:not all quantitative data are statistical. Isolated measurements are not also statistical. Data are statistical when they are related to measurement of masses, not statistical when they are related to an individual item or event as a separate entity.2. Statistics deals only with quantitative characteristics: statistics are numerical statements of facts. Such characteristics cannot expressed in numbers are incapable of statistics analysis.3. statistical results are true only on an average: the conclusion obtained statistically are not universally true; they are true only under certain conditions.4. Statistics is only a means: Statistical methods furnish only one method of studying a problem. They may not provide the vest solution under all circumstances.5. Statistics can be misused: The greatest limitation of statistics is that it is liable to be misused. The misuse of statistics may arise because of several reasons. For example, if statistical conclusion are based on incomplete information, one may arrive at fallacious conclusions.
Alchohol is misused because people drink to much of it and then they drink more and more and more.
what are the most common ways they are misused conjuction,noun,verb,preposition
Alfred nobel invented dynamites which were misused by human beings in wars .
Shouldn't be if not misused.