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Describing scatterplots (form, direction, strength, outliers)
In ABA, scatterplots are commonly used to visually represent data collected during behavioral assessments or interventions. The scatterplot consists of a horizontal x-axis and a vertical y-axis, where each axis represents a different variable being measured.
Scatterplots can visually show the strength of the relationship between the variables (i.e., the scatter in the plot: the more concentrated the dots are along the line, the stronger the relationship); whether there is a positive or negative association between the variables (i.e., whether the slope is positive or
A scatter plot identifies a possible relationship between changes observed in two different sets of variables. It provides a visual and statistical means to test the strength of a relationship between two variables.
The strength of a scatter plot is usually described as weak, moderate or strong. The more spread out the points are, the weaker the relationship. If the points are clearly clustered, or closely follow a curve or line, the relationship is described as strong.

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You interpret a scatterplot by looking for trends in the data as you go from left to right: If the data show an uphill pattern as you move from left to right, this indicates a positive relationship between X and Y. As the X-values increase (move right), the Y-values tend to increase (move up).
If the p-value is less than 0.05, there is a statistically significant correlation between the two variables. The p-value in this example is less than 0.01, so there is a statistically significant correlation between the two.

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