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The Scatterplot is extremely helpful in determining whether or not two variables are correlated (i.e. related). Is Y affected by this X and if so, how strong is the relationship? For example, you may have a hypothesis that there is a relationship between the Number of Days a Nursing Student Studies for their Board Exam (X); and the Score They Receive (Y) . You believe the more days they study, the higher their score will be on the Board Exam. To test your hypothesis, you would collect data from a random sample of Nursing Students who took the Board Exam. Here are the results in a Scatterplot:
As you can see, there does seem to be a strong correlation between Days Studied and Test Scores. There are also two students who did not put a lot of time into studying, but did well on the Board Exam. (Did they do anything differently than the others? Maybe worth investigating?) To quantify the strength of the correlation, you can get an r value. The r value will always range between (-1) perfect negative correlation and (+1) perfect positive correlation ... an r value of (0) tells you there is absolutely no correlation between the two variables. It is important to remember that correlation DOES NOT equal causality. There are more rigorous statistical tests necessary to make that conclusion. |
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Tool Tip - Scatterplot |
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Burns Associates |
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Business Process Improvement Specialists |
