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What is a non resistant measure in statistics?

The mean is called a non-resistant measure in statistics.


What are the 4 levels of measurement in statistics?

5 examples of 4 levels of measurement in statistics


What do the Bureau of Labor Statistics do?

There are many things that the Bureau of Labor Statistics do. Examples of things that he Bureau of Labor Statistics do include collecting, analyzing, and processing economic information.


What The mean median and mode are examples of what type of statistics?

They are measures of location [of a distribution].


Distinguish between parameteric statistics and non - parameteric statistics?

The simplest answer is that parametric statistics are based on numerical data from which descriptive statistics can be calculated, while non-parametric statistics are based on categorical data. Takes two example questions: 1) Do men live longer than women, and 2), are men or women more likely to be statisticians. In the first example, you can calculate the average life span of both men and women and then compare the two averages. This is a parametric test. But in the second, you cannot calculate an average between "man" and "woman" or between "statistician" or "non-statistician." As there is no numerical data to work with, this would be a non-parametric test. The difference is vitally important. Because inferential statistics require numerical data, it is possible to estimate how accurate a parametric test on a sample is compared to the relevant population. However, it is not possible to make this estimation with non-parametric statistics. So while non-parametric tests are still used in many studies, they are often regarded as less conclusive than parametric statistics. However, the ability to generalize sample results to a population is based on more than just inferential statistics. With careful adherence to accepted random sampling, sample size, and data collection conventions, non-parametric results can still be generalizable. It is just that the accuracy of that generalization can not be statistically verified.