## Explore the River:

# Analyzing Data

## Scatter plot graphs

It can be easy to see how one variable changes across space (location) or time. But sometimes the data contain additional relationships. A scatterplot graph can show visually how these additional relationships are connected to the patterns observed in space or time. Scatterplots show whether a relationship between two variables exists, the strength of that relationship, and its direction. They can also show any outliers (data points that don't fit the pattern).

A scatter plot is produced by plotting two variables on an X-Y graph. The independent variable is represented on the X-axis. This is the variable that is presumed to be causing a change. The dependent variable is represented on the Y-axis. This is the variable that is changing as a result of the independent variable. The resulting correlations may be positive (rising), negative (falling), or neither (uncorrelated). If the pattern of dots slopes from lower left to upper right, it indicates a positive correlation between the variables. (An increase in the X value corresponds to an increase in the Y value.) If the pattern slopes from upper left to lower right, it indicates a negative correlation. (An increase in the X value corresponds to a decrease in the Y value.)

You can draw a line of best fit (called a 'trendline') that shows the correlation between the variables. You can then express this relationship in the form of an equation, which is a mathematical model of how the variables are related. The equation can help you estimate values on the X axis for which there are no actual data.

Let's look at two variables that might be related: density of zebra mussels and chlorophyll concentration? Our independent variable (to be graphed along the X-axis) should be the ecosystem component that we think is causing the change. In this case its density of zebra mussels. Our dependent variable (on the Y-axis) is the component that we think is being affected by the independent variable. In this case, the dependent variable is chlorophyll a. The scatterplot shows a negative correlation since the trendline is sloping down. This shows that when the density of zebra mussels increases, chlorophyll a decreases.