The Box Plot , also known as a box diagram , is a graphical and statistical tool that helps us represent changes in data and interpret its variables. Check out this article to learn more about the concept and learn, in just a few steps, how to create a Box Plot in Minitab.
What is a Box Plot?
In statistics, the Box Plot is, in short, a graphical summary of the distribution of a sample . Its graph shows the shape, central tendency and variability of the sample analyzed. Its application is an alternative to other known methods such as the histogram , for example.
What are the elements of a Box Plot?
Box plots are useful for identifying outliers and comparing distributions. There are several ways to construct a box plot, but the first step is to calculate the first quartile, the median, and the third quartile. The bottom line is the first quartile, or the 25% limit of the data. The middle line is the median, and the top line is the third quartile.
Whiskers are vertical lines that end in a horizontal dash. Whiskers are drawn from the upper and lower hinges for the values above and below the first and third quartiles, representing honduras phone number data the maximum and minimum values of the distribution. There are also outliers, which are points whose value is 50% greater than the third quartile or 50% less than the first quartile.
The Box Plot can be placed on a coordinate plane similar to the Cartesian system, so that the five values, arranged vertically one above the other, run parallel to the dependent variable or the y-axis .
In some situations, two or more box plots may be placed side by side on a Cartesian coordinate plane to show how a phenomenon or scenario evolves over time, which is plotted along the independent variable or x-axis . Occasionally, a single box plot is tilted on its side, so the values run from left to right (minimum to maximum) instead of bottom to top.
What is a Box Plot for?
A box plot is a graph used to visually represent the distribution of a data set, showing important information such as the median, quartiles, minimum and maximum values, as well as possible outliers. It is very useful for identifying patterns and characteristics of the data , such as its symmetry, dispersion, central tendency and the presence of extreme values.
It is useful in a variety of fields, such as statistics, data science, engineering, finance, and general research. For example, it can be used to compare the distribution of variables between groups of data, identify outliers in scientific experiments, or analyze the distribution of stock prices in the financial market.
How to interpret the Box Plot?
As its main objective, the Box Plot proposes to verify the distribution of certain data. Therefore, when analyzing its graphical conclusion, we consider the center of the data (mean or median), the range of the data (maximum - upper limit or minimum - lower limit), as well as the symmetry or lack thereof in the data set and the presence of outliers.
Outliers
These are points or asterisks that are outside the “lines” drawn. In other words, it is a value that deviates from the normality of the data and that can, or will, cause anomalies in the results obtained. These discrepant values require the attention of the professional who prepares and analyzes the Box Plot graph, as their interpretation infers great importance for the discussion of the subject represented in the graph.
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