# How are Measures of Dispersion Related to Measures of Central Tendency?

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Measures of dispersion, like standard deviation and interquartile range, give us information about how spread out the data is in a distribution. Measures of central tendency, like mean and median, give us information about where the center of the data is.

###### Mean and Standard Deviation

The mean and standard deviation are often used together because they are based on all of the data values in a distribution. The mean tells us where the center of the data is, and the standard deviation tells us how spread out the data is around the mean.

• For example, if the mean height of students in a class is 5 feet tall with a standard deviation of 2 inches, we know that most students are within 2 inches of the mean height.

###### Median and Range

The median and interquartile range are often used together because they are based on the middle 50% of the data values in a distribution. The median tells us where the center of the data is, and the interquartile range tells us how spread out the data is around the median.

• For example, if the median income of a group of people is \$50,000 with an interquartile range of \$20,000, we know that most people have an income within \$20,000 of the median.

Conversely, the range is not based on any measure of central tendency because it only looks at the minimum and maximum values in a distribution. The range tells us the distance between the smallest and largest values, but it doesn’t tell us where the center of the data is or how spread out the data is around the center.

###### Quartiles

Quartiles are values that divide a data set into four equal parts, each containing 25% of the data points. There are three quartiles commonly used:

• First Quartile (Q1): This is the 25th percentile, which separates the lowest 25% of the data from the rest. It is the value below which 25% of the data falls.
• Second Quartile (Q2): Also known as the median, this is the 50th percentile, dividing the data into two equal halves. It is the middle value when the data is arranged in ascending order.
• Third Quartile (Q3): This is the 75th percentile, separating the lowest 75% of the data from the highest 25%. It is the value below which 75% of the data falls.

When quartiles are aligned with the median, the second quartile (Q2) is exactly the same as the median. This means that Q2 divides the data into two equal halves, with 50% of the data points falling below it and 50% above it. In this case, the first quartile (Q1) is the median of the lower half of the data, and the third quartile (Q3) is the median of the upper half of the data. This alignment provides a clear picture of how the data is distributed around the median, making it useful for understanding the central tendency of the dataset.

In summary, measures of dispersion give us information about how spread out the data is, while measures of central tendency give us information about where the center of the data is. The mean and standard deviation are often used together, as are the median and interquartile range. The range does not correspond with any measure of central tendency.