Can statistics be misleading?

There is an old saying that the numbers do not lie, but liars know how to come. In a sense, this represents the alert statistics of people. Statistical interpretation can cause data to appear to be misleading. It depends on the interpretation of data statistics and what data is brought to the foreground as on key points of statistical reports. The diameter is the sum of all data divided by the number of data. For example, one could get the sum of the person's test and divide it by the number of tests to determine the mark. However, the average may be influenced by what is called a remote, number beyond the normal testing range. This may indicate that the average may be a misleading way of performance assessment. If all tests are worth 100 PNA ointments, the average score is approximately 85%. In this case, however, this does not actually indicate the average power due to remote zero.

Another measure of the central tendency that can beUsed is the evaluation of the median. The median is a middle number in a group of data organized numerically. If the statistics evaluate the median, it may not be representative for the actual performance diameter or everything that is evaluated. The median cannot be responsible for the range of data that can be huge and can therefore be misleading.

Central tendencies evaluated by mode means only when looking at the number that occurs most often in the data set. For example, the test has 100 mode.

Other ways that statistics can be misleading is the way in which they may be in a survey and measure, the survey of a representative sample of the community. If someone examines a group of secondary school students and asks, "How happy are you with your education on a scale of 1-5?" One can get very different answers depending on whether the group is representative of the "average" student.

If one examines a group of students who all get straight and go to a fantastic, well -funded SKOly to publish such data as a representative sample must be deliberately misleading. If you ask students of different schools with different grades, then the survey is likely to be more representative and faire. However, if a person asks students what schools think and then publish the results as a representative sample of the general population, the answers will then be very distorted.

The

numbers may seem very concrete and some of them are simply mentioned in the mistakes of the numbers simply because they seem to be a fact and have an indisputable value. Such statistical data can often be used in a misleading manner so that people with numbers are tossed with numbers, and things in the dispute look more like a reality. Renowned statisticians know that the questions need to be generalized and must also be placed on people who represent populations.

However,

numbers and statistics can be misleading because they do not represent individuals. Can show how people "generally" respond to the idea, product or political candidatethe. They cannot show how the only person will feel in all their infinitely variable qualities.