## What graph does median and IQR have?

### The median and interquartile range (IQR) are statistics that are commonly used to describe the center and spread of a dataset, particularly in statistics and data analysis

The median and interquartile range (IQR) are statistics that are commonly used to describe the center and spread of a dataset, particularly in statistics and data analysis.

The median is a measure of central tendency and represents the middle value of a dataset when it is arranged in increasing or decreasing order. To find the median, you simply need to locate the value that splits the dataset into two equal halves. If the dataset has an odd number of values, the median will be the middle value. If the dataset has an even number of values, the median will be the average of the two middle values.

The interquartile range (IQR) is a measure of dispersion and represents the range of the middle 50% of the dataset. It is calculated as the difference between the upper quartile (Q3) and the lower quartile (Q1) of the dataset. The quartiles are values that divide a dataset into four equal parts. Q1 represents the 25th percentile (i.e., 25% of the values are below it) and Q3 represents the 75th percentile (i.e., 75% of the values are below it).

Both the median and IQR are useful in summarizing data and providing insights into its distribution and variability. When it comes to graphing the median and IQR, the most common approach is to use a box plot or a box-and-whisker plot.

A box plot is a graphical representation that displays the median as a line within a box. The lower boundary of the box represents Q1, and the upper boundary represents Q3. The box encapsulates the IQR. Typically, there are whiskers extending from the box that indicate the range of the data (excluding any outliers). Outliers, which are extreme values, are often plotted as individual points beyond the whiskers.

By visualizing the median and IQR using a box plot, you can quickly understand the center and spread of a dataset, identify any outliers, and compare different datasets or groups.

##### More Answers:

The Implications and Characteristics of a Large Standard Deviation in Data Analysis.The Importance of Using the Median Instead of the Mean for Skewed Data and Outliers

Understanding Standard Deviation | A Statistical Measure for Analyzing Data Variability and Making Informed Decisions