box plot ?

If your asking what a box plot is you can go to the following site and get your answer.

http://en.wikipedia.org/wiki/Box_plot

http://www.khanacademy.org/math/probability/descriptive-statistics/Box-and-whisker%20plots/v/box-and-whisker-plots

thank a lot :0

A box plot, also known as a box and whisker plot, is a type of visualization that provides a summary of a set of data values. It displays the minimum, lower quartile, median, upper quartile, and maximum values in a concise and easy-to-understand format.

To create a box plot, follow these steps:

1. Organize your data set: Start by sorting your data in ascending order.

2. Find the median: Determine the median (middle) value of your data set. If you have an odd number of data points, the median is the middle value. If you have an even number of data points, the median is the average of the two middle values.

3. Find the quartiles: Divide your data set into four equal parts, known as quartiles. The lower quartile (Q1) is the median of the lower half of the data, excluding the median. The upper quartile (Q3) is the median of the upper half of the data, excluding the median.

4. Determine the interquartile range (IQR): Calculate the difference between the upper quartile (Q3) and the lower quartile (Q1). This range represents the middle 50% of the data.

5. Identify outliers: Outliers are data points that lie outside the range of the whiskers in a box plot. They can be determined using various statistical methods, such as the 1.5 * IQR rule or the modified Z-score method.

6. Create the box plot: Draw a vertical line from the minimum value to the lower quartile (Q1) and then draw a box from Q1 to the median value. Next, draw another vertical line from the median to the upper quartile (Q3), and finally draw a vertical line from Q3 to the maximum value. The resulting plot will show the distribution of the data and any outliers.

Box plots are useful for comparing data sets and identifying skewness, variability, and outliers. They provide a clear visual representation of the central tendencies and spread of the data.