Scatter Diagrams

Scatter Diagrams

What is a Scatter Diagram?

The scatter diagram also known as X-Y graph, scatter plot, scatter graph or correlation chart is a graph plotted from two variables, an independent (common cause) variable on the X-axis and a dependable (effect) variable on the Y –axis. If the variables are related, the better the connection and the closer the points will hug the line. It is also important to note that the Scatter diagram is one the seven basic tools of quality.

Purpose:

  • To examine the possible relationship between the changes observed in two different sets of variables
    • To see if as one measurement changes the other increases or decreases
  • To determine the relationship between two measurements when you have paired numerical data.
  • When your dependent variable may have multiple values for each value of your independent variable.
  • To determine whether a cause and effect are related.
  • When trying to identify potential root causes of problems.
  • When determining whether two effects that appear to be related both occur with the same cause.

Example of When a Scatter Diagram Can Be Used

  • A scatter diagram can be used to identify the relationship between highway driving speeds and the number of speeding tickets issued by the police

Types of Scatter Diagrams

1. Positive Correlation

As one variable increases, the other increases. Level of education and remuneration are an example. The more education years you complete, the higher your earning potential.

 1-3.png

2. Negative Correlation

As one variable decreases, the other decreases. When two variables have a negative correlation, they have an inverse relationship. Inflation and purchasing power are an example. The higher the inflation the lower the purchasing power.

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3. No Correlation

When both (X and Y) variables are not related, the data set has no correlation.

 

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How to Construct a Scatter Diagram

  •  Collect two pieces of data and create a summary table of the data
  • Draw a diagram labeling the horizontal and vertical axes.
    • It is common that the “cause” (independent) variable be labeled on the X axis and the “effect” (dependent) variable be labeled on the Y axis.
  • Plot the data pairs on the diagram
    • For each pair of data, put a dot or a symbol where the x-axis value intersects the y-axis value. (If two dots fall together, put them side by side, touching, so that you can see both.)
  • Interpret the scatter diagram for direction and strength.

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