The way of representation of numeric variables and the distribution of a set of data is known as a box plot. But with the help of a box plot calculator, you can get a graphic display that gives powerful distribution insights. In Whisker, the plot consists of a box that is rectangular shaped and has verticle lines that indicate the median as well as displaying the range of data which excludes outliers.
With the help of a box and whisker plot calculator, you can also captivate the variable locations and get the answer with remarkable clarity so we can say that it is a powerful data exploration and analysis tool.
Let us move on toward the depth discussion to explore the graphic display of various locations and know about their applications. Stay focused and read on!
The box plot is a way to summarize the set of data in the form of a graph. The box plot shape indicates how the data is distributed and how this data is gathered. In this way, you can compare the data set with others by sketching more boxplots on the graph.
“In a simple and comprehensive tone, we say that in statistics the type of chart that shows a group of numerical data is called a box plot.” The other name of the box plot is the whisker plot. You can summarize the set of data with the help of a box plot calculator.
With the help of a box plot calculator, you can get a quick summary of different values in the data set. It shows the fast calculations by representing the median, upper and lower quartiles as well as their minimum and maximum values in the dataset.
There are two most commonly used types of box plots that are as follows:
The box plot calculator allows you to generate the sketch from the set of statistical data. Follow the below points and explore how this daunting task is done.
Example:
Suppose a dataset 55, 62, 35, 32, 50, 57, 54 and we need to estimate the distribution of the data set and draw their sketch.
Solution:
The Strengths of Box Plot:
A box plot calculator is a way to understand the statistical data and allows you to create a diagram to clarify the concept. The strengths mean their applications are in the below-given points. Look at these:
Graphic Representation of a Dataset:
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