Scatter Diagrams and its Implementation

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NEO Fri, Feb 04, 2022 12:05 PM UTC

This pdf includes the following topics:-
Scatter Diagrams
When to use Scatter Diagrams
How to use Scatter Diagrams
Interpret the data
Correlation and many more.

1. SCATTER DIAGRAM
A scatter diagram is a tool for analyzing relationships between two variables. One
variable is plotted on the horizontal axis and the other is plotted on the vertical axis. The
pattern of theirintersecting points can graphically show relationship patterns. Most often
a scatter diagram is usedto prove or disprove cause-and-effect relationships. While the
diagram shows relationships, itdoes not by itself prove that one variable causes the
other. In addition to showing possible causeand-effect relationships, a scatter diagram
can show that two variables are from a common causethat is unknown or that one
variable can be used as a surrogate for the other.
When to use it:
Use a scatter diagram to examine theories about cause-and-effect relationships and to
search for root causes of an identified problem. Use a scatter diagram to design a
control system to ensure that gains from quality improvement efforts are maintained.
How to use it:
Collect data. Gather 50 to 100 paired samples of data that show a possible
Draw the diagram. Draw roughly equal horizontal and vertical axes of the diagram,
creating a square plotting area. Label the axes in convenient multiples (1, 2, 5, etc.)
increasing on the horizontal axes from left to right and on the vertical axis from bottom
to top. Label both axes.
Plot the paired data. Plot the data on the chart, using concentric circles to indicate
repeated data points.
Title and label the diagram.
Interpret the data.
Scatter diagrams will generally show one of six possible correlations between the

2. Strong Positive Correlation
The value of Y clearly increases as the value of X increases.
Strong Negative Correlation
The value of Y clearly decreases as the value of X increases.
Weak Positive Correlation
The value of Y increases slightly as the value of X increases.
Weak Negative Correlation
The value of Y decreases slightly as the value of X increases.
Complex Correlation
The value of Y seems to be related to the value of X, but the relationship is not easily
No Correlation
There is no demonstrated connection between the two variables.
Scatter Diagram Example
Strong Positive Correlation

3. Strong Negative Correlation
Weak Positive Correlation
Weak Negative Correlation

4. Complex Correlation
No Correlation

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