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Introduction to Correlational Studies
You have learned that correlation research helps scientists understand the relationship(s) between
variables. You have also learned that this analysis can be performed if you can obtain interval or
ratio scale measurements on several variables. This implies you must measure more than one
variable for each person, and this must be done for several people.
Returning to the hypothetical study on the relationship between the amount of caffeine ingested
and the level of alertness, suppose you were intrigued by this idea and decided to examine the
relationship between these two variables in a study. Let's see the results of this research by
means of a graphic.
An Example of a Correlational Study
You recruit 15 people to participate in a study to examine the relationship between the amount of
caffeine ingested and the level of alertness. The 15 participants are not allowed to drink anything
on the morning of the test until 10 a.m. At that time, they can only drink water, coffee, or tea.
Only they must come into a laboratory to get the drinks, and their meals will also be
administered to monitor the type and amount of food ingested. Research assistants record the
amount and type of drink they consumed. The participants would be allowed to start drinking at
10 a.m. and the level of alertness would be tested 60 minutes after starting the fluid consumption.
Alertness was tested using two different measures. One was a physiologically based measure that
looked at eye pupil size after sitting in five minutes of darkness. This assessment is based on the
principle that pupils contract or get smaller when a person is sitting in the dark and/or when
alertness decreases. The pupil size can range from 0 to about 5 millimeters.
See linked documents for examples of how and when to use correlation.

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Introduction to Correlational Studies You have learned that correlation research helps scientists understand the relationship(s) between variables. You have also learned that this analysis can be performed if you can obtain interval or ratio scale measurements on several variables. This implies you ...
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