Suppose you have a data set as shown below, where I have 20 companies with their revenue and profit margin numbers. This usually works well when you have a diverse data set with less overall correlation. One of the ways I used to use scatter charts in my work as a financial analyst was to identify clusters of data points that exhibit a similar kind of behavior. Identifying Clusters using Scatter Chart (Practical Examples) In our example, it returns 0.945, indicating that these two variables have a high positive correlation. The correlation coefficient varies between -1 and 1, where 1 would indicate a perfectly positive correlation and -1 would indicate a perfectly negative correlation You can find that using the below formula: =CORREL(B2:B11,C2:C11) This is something that can be calculated using the correlation coefficient.
it doesn’t tell us how closely it’s related.įor example, in our example, by looking at the trendline we cannot say how much the revenue will go up when the marketing expense increases by 100%. Note that the slope only tells us whether the data is positively or negatively correlated. In this case, when the marketing expenses increase, their revenue may or may not increase.
In that case, if the marketing expenses go up then the revenue would go down and vice versa.Īnd then there is a case where there is no correlation. In case the data is negatively correlated, then there would be an inverse relation. This means that when the marketing expenses go up then the revenue goes up and if the marketing expenses go down then the revenue goes down. In our example, we see a positive slope in the trendline indicating that the data is positively correlated. Just by looking at the trendline and the data points plotted in the scatter chart, you can get a sense of whether the data is positively correlated, negatively correlated, or not correlated. Scatter chart with a linear trendline (dotted line) Suppose you have a dataset as shown below and you want to create a scatter plot using this data. Revenue) in a scatter chart, we can analyze how strongly or loosely these two variables are connected. When we plot this data (Marketing Expense vs. Scatter charts are used to understand the correlation (relatedness) between two data variables.Ī scatter plot has dots where each dot represents two values (X-axis value and Y-axis value) and based on these values these dots are positioned in the chart.Ī real-life example of this could be the marketing expense and the revenue of a group of companies in a specific industry.
What is a Scatter Chart and When To Use It?
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