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Which Measures Of Center And Spread Are Affected By Outliers Pdf

which measures of center and spread are affected by outliers pdf

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Measures of location describe the central tendency of the data. They include the mean, median and mode. Their calculation is described in example 1, below.

Recall the five-number summary from Example 3. In our example,. What does this IQR represent? The IQR is the length of the box on a boxplot.

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Why do we care? One application is testing for normality : many statistics inferences require that a distribution be normal or nearly normal. A normal distribution has skewness and excess kurtosis of 0, so if your distribution is close to those values then it is probably close to normal. If the bulk of the data is at the left and the right tail is longer, we say that the distribution is skewed right or positively skewed ; if the peak is toward the right and the left tail is longer, we say that the distribution is skewed left or negatively skewed. Look at the two graphs below. The beta distribution is one of the many skewed distributions that are used in mathematical modeling.

Outliers Sparknotes Chapter 5

The measures of central tendency are not adequate to describe data. Two data sets can have the same mean but they can be entirely different. Thus to describe data, one needs to know the extent of variability. This is given by the measures of dispersion. Range, interquartile range, and standard deviation are the three commonly used measures of dispersion.

The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean average and the median. To calculate the mean weight of 50 people, add the 50 weights together and divide by To find the median weight of the 50 people, order the data and find the number that splits the data into two equal parts. The median is generally a better measure of the center when there are extreme values or outliers because it is not affected by the precise numerical values of the outliers.


Spread is measured either by the mean and standard deviation (the spread of the data median as the measure of center because it is not affected by outliers.


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In statistics , dispersion also called variability , scatter , or spread is the extent to which a distribution is stretched or squeezed. Dispersion is contrasted with location or central tendency , and together they are the most used properties of distributions. A measure of statistical dispersion is a nonnegative real number that is zero if all the data are the same and increases as the data become more diverse. Most measures of dispersion have the same units as the quantity being measured. In other words, if the measurements are in metres or seconds, so is the measure of dispersion.

Documentation Help Center. The purpose of measures of dispersion is to find out how spread out the data values are on the number line. Another term for these statistics is measures of spread. The range the difference between the maximum and minimum values is the simplest measure of spread.

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Measures of dispersion

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1 Comments

  1. Sophie W.

    25.04.2021 at 17:35
    Reply

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