          What is it: A Scatter Diagram or also called scatter plot or a X–Y graph is used to identify relationships between two process variables. Use a Scatter Diagram to determine if there is correlation between two characteristics. Correlation implies that as one variable changes, the other also changes. Although this may indicate a cause and effect relationship, this is not always the case, since there may be a third characteristic (or many more) that are actually the cause, and both the characteristics of interest are the effect. Sometimes, though, if we know that there is good correlation between two characteristics, we can use one to predict the other, particularly if one characteristic is easy to measure and the other isn't.

Why use it: To confirm that two variables have a relationship.

Where to use it:

• When you have paired numerical data.
• When your dependent variable may have multiple values for each value of your independent variable.

When to use it:

• When trying to determine whether the two variables are related.
• When trying to identify potential root causes of problems.
• After brainstorming causes and effects using a fishbone diagram, to determine objectively whether a particular cause and effect are related.
• When determining whether two effects that appear to be related both occur with the same cause.
• When testing for autocorrelation before constructing a control chart.
• When the team thinks that one variable is dependent on another.

How to use it: A Scatter graph or scatter plot is a type of display using Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. When drawing a scatter diagram the first step is too look for a relationships between the variables, a line of best fit is usually drawn through the points, particularly where there is a strong correlation. If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line.

#### Important Notes:

• Even if the scatter diagram shows a relationship, do not assume that one variable caused the other. Both may be influenced by a third variable.
• When the data are plotted, the more the diagram resembles a straight line, the stronger the relationship.
• If a line is not clear, statistics (N and Q) determine whether there is reasonable certainty that a relationship exists. If the statistics say that no relationship exists, the pattern could have occurred by random chance.
• If the scatter diagram shows no relationship between the variables, consider whether the data might be stratified.
• If the diagram shows no relationship, consider whether the independent (x-axis) variable has been varied widely. Sometimes a relationship is not apparent because the data don’t cover a wide enough range.
• If investigating dependence, set the independent variable on the x-axis and the dependent variable on the y-axis.

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