What does a scatter plot tell you?
Scatter plots are similar to line graphs in that they use horizontal and vertical axes to plot data points. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation .
No association: Hard to find a pattern showing a relationship between the variables. STEP 1: Make a scatterplot; describe the form, direction and strength of the relationship. Before doing the scatterplot you need to decide which variable is the explanatory variable and which is the response variable.
- Negative correlation is a relationship between two variables in which one variable increases as the other decreases, and vice versa. In statistics, a perfect negative correlation is represented by the value -1.00, a 0.00 indicates no correlation, and a +1.00 indicates a perfect positive correlation.
- Scatter Plots. A Scatter (XY) Plot has points that show the relationship between two sets of data. In this example, each dot shows one person's weight versus their height. (The data is plotted on the graph as "Cartesian (x,y) Coordinates")
- A negative correlation is a relationship between two variables such that as the value of one variable increases, the other decreases. Correlation is expressed on a range from +1 to -1, known as the correlation coefficent.
Positive correlation is a relationship between two variables in which both variables move in tandem. A positive correlation exists when one variable decreases as the other variable decreases, or one variable increases while the other increases.
- Recall, Positive/Negative Association: • Two variables have a positive association when the values of one variable tend to increase as the values of the other variable increase. • Two variables have a negative association when the values of one variable tend to decrease as the values of the other variable increase.
- A negative correlation is a relationship between two variables such that as the value of one variable increases, the other decreases.
- A perfect positive association means that a relationship appears to exist between two variables, and that relationship is positive 100% of the time. In statistics, a perfect positive association is represented by the value +1.00, while a 0.00 indicates no association.
Updated: 2nd October 2019