What is the outcome of using scatterplots in research?

Using scatterplots in research serves primarily to visualize the relationship between two variables. A scatterplot is a graphical representation that displays individual data points plotted along two axes, corresponding to the values of the two variables being examined. By plotting these points, researchers can quickly observe patterns, trends, and correlations, which allows them to assess how the variables may relate to each other.

This visualization enables the identification of various types of relationships—be it positive, negative, or none—between the variables. For instance, if the points are grouped closely along an upward slope, this suggests a strong positive correlation; if they scatter in a downward slope, that indicates a negative correlation. This exploratory data analysis is crucial in forming hypotheses for further research or guiding practical applications based on observed trends.

The other options pertain to different research goals or methods. While determining causation is a more complex process that involves controlled experimentation and is not achievable through scatterplots alone, the identification of experimental groups and variability measurement generally pertains to experimental design rather than visualization techniques. Therefore, the primary outcome of employing scatterplots lies in their ability to effectively illustrate relationships between variables.