![]() ![]() Combining those time periods in a single scatter diagram may make interpretation more difficult. If the dots are scattered all over the graph then there is no evidence for a relationship between the variables.Īs with Pareto charts and frequency plots, separate scatter plots can helpfully be used to understand the difference between time periods with only random (common cause) variation and those with non-random (special cause) variation (identified using Shewhart control charts). This may also suggest a cause and effect relationship for further investigation. If the vertical variable decreases as the horizontal one increases we say there is negative correlation. Basically, when you closely examine the graph, you will see that the graph. This may indicate cause and effect but it may not be that simple. When y decreases as x increases, the two sets of data have a negative correlation. If the vertical variable increases as the horizontal one does (as the example above shows) then we say there is a positive correlation. One variable is plotted on the horizontal axis (usually the one that you are trying to control) and the other on the vertical axis (usually the one you expect to respond to the changes you are making). This may also suggest a cause and effect relationship. Similar to a straight line with a negative gradient. Scatter plots show the relationship between the two variables in pairs of observations. If the vertical variable decreases as the horizontal one increases we say there is negative correlation. A negative correlation is when the data appears to gather in a negative relationship. ![]() ![]() A scatter plot is a graph used to look for relationships between two variables How to use it ![]()
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