It looks like a straight line increasing as the x-values increase. So basically a line that goes from the bottom left area to the top right area on a graph.
You can look at the r value and tell from there. Also you can try to see if there is a linear assocation and if its tightly centered or loosely centered.
Strength and direction of linear relation. Closer to 1 is positive linear association, closer to -1 is positive negative association and closer to 0 means no linear relation. Remember that 0 does not mean that there is no relation - just no linear relation.
You cannot. Or rather, you should not. You do not know if the relationship is linear or something else. A scatter graph is the best way to establish the nature of the relationship. For example, the correlation between x and y, when y = x2 between, say, -4 and +4 is zero (because of symmetry). That would lead you to conclude that there was no relationship. You could not be more incorrect!
The closer the correlation is to 1 or -1, the more linear the data is
A negative correlation is a measure of the linear component of a relationship where one variable increase as the other decrease.
The product-moment correlation coefficient or PMCC should have a value between -1 and 1. A positive value shows a positive linear correlation, and a negative value shows a negative linear correlation. At zero, there is no linear correlation, and the correlation becomes stronger as the value moves further from 0.
If the two variables increase together and decrease together AND in a linear fashion, the correlation is positive. If one increases when the other decreases, again, in a linear fashion, the correlation is negative.
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Scatter-plot shows correlation between two different variables (one on the y-axis, the other on x-axis). If there is linear correlation, the scatter-points form a straight line from zero (origo) to some direction. The more cloud-like distribution the scatter-plot does have, the less those variables in question have correlation or dependence with each other.
No, it is not possible to make accurate predictions based on a scatter plot with no correlation. A scatter plot with no correlation means that the data points are randomly scattered and do not follow any specific pattern or trend. Without a correlation, it is difficult to establish a relationship between the variables and make reliable predictions.
If the data have a positive or negative correlation, it means the data have a linear relationship in the form of an equation of a line; or Y = mX + b.
False.
No. If the correlation coefficient is close to 1 or -1, then the two variables have a high degree of statistical linear correlation. See the related link, particularly the graphs which illustrate correlation.
You can look at the r value and tell from there. Also you can try to see if there is a linear assocation and if its tightly centered or loosely centered.
Strength and direction of linear relation. Closer to 1 is positive linear association, closer to -1 is positive negative association and closer to 0 means no linear relation. Remember that 0 does not mean that there is no relation - just no linear relation.
No, it's not consider as a linear scatter plot, because, it's non-linear.
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