d) the variance equals the standard deviation. 8. When extreme values are present in a set of data, which of the following descriptive summary measures are most appropriate: a) CV and range.
Extreme values (otherwise known as 'outliers') are data points that are sparsely distributed in the tails of a univariate or a multivariate distribution. The understanding and management of extreme values is a key part of data management.
Arithmetic mean refers to the average amount in a given group of data. It is defined as the summation of all the observation in the data which is divided by the number of observations in the data. Therefore, mean is affected by the extreme values because it includes all the data in a series. Was this answer helpful?
The median may be more useful than the mean when there are extreme values in the data set as it is not affected by the extreme values. The mode is useful when the most common item, characteristic or value of a data set is required.
The Extreme value theorem states that if a function is continuous on a closed interval [a,b], then the function must have a maximum and a minimum on the interval.
Extreme value analysis (EVA) is a statistical tool to estimate the likelihood of the occurrence of extreme values based on a few basic assumptions and observed/measured data.
5 ways to deal with outliers in dataSet up a filter in your testing tool. Even though this has a little cost, filtering out outliers is worth it. ... Remove or change outliers during post-test analysis. ... Change the value of outliers. ... Consider the underlying distribution. ... Consider the value of mild outliers.
There are four ways to identify outliers:Sorting method.Data visualization method.Statistical tests (z scores)Interquartile range method.
Arithmetic mean is most affected by extreme (minimum and maximum) items of the data.
How might an extreme value in the sample data set affect the value of the mean? All values are treated equally when determining the mean so an extreme value cannot affect it.
The meanThe mean is sensitive to extreme scores. For example, the mean of the following data is 39.0, somewhat larger than the preceding example. In most cases the mean is the preferred measure of central tendency, both as a description of the data and as an estimate of the parameter.
The medianWhat is the most appropriate measure of central tendency when the data has outliers? The median is usually preferred in these situations because the value of the mean can be distorted by the outliers.