A handful of **scatter diagrams **in high definition has been collected for you! These diagrams are free to be saved and printed in larger size. People usually use scatter diagrams to represent and compare two sets of data. By looking at a scatter diagram, we can see whether there is any connection (correlation) between the two sets of data. Look at the first image of the diagram below.

Well, the scatter diagram graphs pairs of numerical data, with one variable on each axis, to look for a relationship between them. If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line. A scatter plot can suggest various kinds of correlations between variables with a certain confidence interval. For example, weight and height, weight would be on y axis and height would be on the x axis. Correlations may be positive (rising), negative (falling), or null (uncorrelated). If the pattern of dots slopes from lower left to upper right, it indicates a positive correlation between the variables being studied. If the pattern of dots slopes from upper left to lower right, it indicates a negative correlation, as you can see in the following *scatter diagrams *posted below.

So when do we use a scatter diagram? Well, you can use it when you have paired numerical data, when your dependent variable may have multiple values for each value of your independent variable, when trying to determine whether the two variables are related, such as when you are trying to identify potential root causes of problem; after brainstorming causes and effects using a fishbone diagram, to determine objectively whether a particular cause and effect are related; when determining whether two effects that appear to be related both occur with the same cause; when testing for autocorrelation before constructing a control chart.

That’s why we provide you with a variety of the diagrams to give you a glimpse on how the diagram can be used. All the pictures are free and printable so just click on the image to save it. See ya!