What is the meaning of no correlation in a scatter diagram?

No correlation in a scatter diagram means there is no apparent relationship between the two variables being compared.

In a scatter diagram, data points are plotted on a graph to show the relationship between two variables. When we say there is "no correlation," it means that the points do not form any discernible pattern. They are scattered randomly across the graph, indicating that changes in one variable do not predict changes in the other.

For example, imagine you are comparing the number of hours students study and their shoe sizes. If you plot this data on a scatter diagram and find that the points are all over the place with no clear trend, this would indicate no correlation. In other words, knowing a student's shoe size gives you no information about how many hours they study.

In mathematical terms, no correlation means the correlation coefficient (a number that quantifies the degree of relationship between two variables) is close to zero. This coefficient ranges from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 indicates no correlation.

Understanding no correlation is important because it helps you recognise when two variables are independent of each other. This can prevent you from making incorrect assumptions or predictions based on unrelated data. So, when you see a scatter diagram with no clear pattern, you can confidently say that the variables do not influence each other.