![]() ![]() The temperature will be plotted onto the x-axis, while ice cream sales will go on the y axis. Now that we have the raw data before us, the next step is to plot this data onto a graph. Here’s what their raw data looks like for the past 10 days. Ice-cream shop XYZ keeps track of the number of ice creams they sell depending on the noon temperature of the day. ![]() Let’s look at an example of a scatter diagram to better understand how they work. Outlier points are also more easily identified with this trendline. When the relationship between the two variables is strong, this line helps make that even more evident. This trend line helps identify any trends that may be taking place on the scatter plot. There is no relationship between the two variables.Īlthough the value of X and Y are related to each other, and the relationship is not easily determined.Ī-Line of Best Fit can be used on a scatter diagram. These are also the types of scatter diagrams.Īs the value of X increases, the value of Y increases.Īs the value of X increases, the value of Y increases slightly.Īs the value of X decreases, the value of Y decreases.Īs the value of X decreases, the value of Y decreases slightly. ![]() The table below outlines the different correlation patterns identified in a scatter plot. When the points are scattered all over the chart, the degree of correlation is low, i.e., they are very related. When points are plotted close to each other, there is a high degree of correlation, i.e., they are closely related to one another. This degree of correlation is denoted by the symbol ‘r’. Scatter diagram correlation Patterns and TypesĬorrelation between the data points can be identified based on how spread the points are. Outliers and unexpected data gaps can also be easily identified. This is very handy for when the data needs to be segmented. Depending on how close the data points are, they can be divided into further groups.
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