**Scatter diagram** or **scatter plot** displays the statistical correlation (dependence) between two measured variables. The pairs of variables are plotted on the graph as points that are subsequently analysed in terms of density and direction of correlation.
The variables can either be dependent or independent on each other. Every pair of the measured variables is plotted as one point. The density of the points in the diagram shows the level of their correlation - less dense the points are, the weaker is the correlation between the variables. Places with the biggest density determine the direction of the correlation that is depicted by a line or a curve.

- displays two independent or dependent variables
- usually, one of the variables has an impact on the other one (for example, age of customers influences their shopping habits)
- represented by points
- the pattern (density of the dots) is subject to further analysis

Scatter diagram is the simplest way of determining the correlation between two variables.

## What is the scatter diagram used for in practice?

The scatter plot is the simplest tool that is used every time that there are some input data available (usually some statistics) and we need to make a graphic **analysis of correlation between two variables**. This can be sales data, such as customer satisfaction or price sensibility, or, for example, data about quality in production (scatter diagram is among the 7 core quality management tools).

The data comes from, for example, observation, questionnaires, surveys and so on. The more data we have, the more exact the diagram is. The absolute minimum is 6 points. The diagram can be used repeatedly to compare the measured variables (every day, week, month, etc.) in order to find out about the trends in direction of correlation.

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