## Overview

A graphical presentation helps us organize data and examine their quality. It will be useful later to envisage the population from which the sample is drawn. All the graphics generated in this site can be exported by copy-and-paste ([Ctrl-C] and [Ctrl-V] at the place you choose to export).

- Histogram is used to present a sample distribution for numerical data.
- Stem and leaf plot split each value of the numerical data into a ``stem'' and a ``leaf,'' and displays them separately. The advantage of this plot is that we do not lose information on individual observation.
- Boxplot gives a graphical presentation of summary statistics.

The exploratory graphics are also useful for identifying odd-looking values which do not fit in with the rest of the data. In the graphical presentation of data such values appear to be quite separate from the rest of the data, and are called outliers. In many cases outliers are discovered to be misrecorded data values, or represent some special condition that was not in effect when the data were collected.

Other graphical techniques will be introduced later for different purposes and functionality.

- Scatter plots are needed for studying the relationship between two variables.
- QQ-plot is used to determine whether sample data is approximately normal or not.
- Bar graph is used to illustrate data when the variable of interest is categorical.

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