![]() ![]() In this type of graph, both variables have an almost linear relationship. Image Source: Perfect Positive Correlation Scatter Chart with Weak Positive Correlation The data points in this chart form a straight line.įor example, if are to compare, the number of people who buy movie tickets and the money spent on buying them, we will get a straight line. The variables are said to have a positive slant and thus the chart is called “Scatter Diagram with a Positive Slant”. The variable change is proportional, so as one variable increases, so does the other. In this type of scatter chart, the correlation between the variables plotted is strong. Scatter Chart with Strong Positive Correlation Scatter Chart with Weak Negative Correlation.Scatter Chart with Strong Negative Correlation.Scatter Chart with Weak Positive Correlation.Scatter Chart with Strong Positive Correlation.Scatter charts can also be categorized based on slopes, changes, or data points. ![]() Image Source: Scatter chart with No correlation This chart is also called “Scatter Diagram with No Degree of Correlation”. In this type of chart, it can be observed that data points are scattered all over the place and no relation can be made from them. Image Source: Scatter chart with moderate correlationĪlso Read: All about Doughnut Charts and their uses Scatter chart with No correlation This chart is also known as “Scatter Diagram with a Low Degree of Correlation”. Nevertheless, it can be observed that a certain kind of relation exists between the variables. They are not fully linear, and you cannot draw a straight line through them. In this type of chart, the data points are arranged somewhat closer to each other. Image Source: Scatter Charts with strong correlation Scatter chart with moderate correlation This chart is also called “Scatter Diagram with a High Degree of Correlation”. Thus, denoting the strong correlation between the data. Then we can observe that all the markers or data dots are closely arranged in a linear way, such that a line can be drawn by joining them. In this type of chart, the data is plotted in dots, keeping the dependent variable in the y-axis and independent variable in the x-axis.
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