Scatterplots & Correlation Coefficients: Learn It 2

  • Create scatterplots for bivariate data and answer questions from the graph.
  • Describe the trend of bivariate data.
  • Calculate the correlation coefficient and explain what it means.

Interpreting a Scatterplot

How do we describe the relationship between two quantitative variables using a scatterplot? We describe the overall pattern and deviations from that pattern. To describe the overall pattern of the distribution of one quantitative variable, we describe the shape, center, and spread. We also describe deviations from the pattern (outliers).

Flowchart of graphing the distribution of 2 quantitative variables in a scatterplot, which includes overall patterns and derivations from the patterns
Figure 1. When analyzing a dotplot, describe the overall pattern (direction, form, strength) and look for deviations, or outliers, that don’t follow the pattern.

Similarly, in a scatterplot, we describe the overall pattern with descriptions of direction (trend), form (linear or non-linear), and strength. Deviations from the pattern are still called outliers.

Identifying Trends/Directions

Identifying patterns in scatterplots can help us determine if a relationship exists between two variables. Scatterplots might show positive trends, negative trends, or no trends at all.

A scatterplot shows a positive trend if the response variable (represented on the vertical axis) tends to increase as the explanatory variable (represented on the horizontal axis) increases. Conversely, if the response variable tends to decrease as the explanatory variable increases, then the scatterplot shows a negative trend.