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Scatter Plot


Scatter plots are a kind of scatter diagram that shows the relationship between two variables. If x and y are the two variables, then the scatter diagram shows the location of the points (x, y) on a rectangular coordinate system. Thus, a Scatter plot shows the correlation, or the degree of relationship between two variables, which seeks to determine how well a linear or other equation, describes or explains the relationship between the variables. We can determine, how a given line or curve describes the relationship between variables by direct observation of the scatter diagram itself. That is why; this kind of study of correlation between two variables is known as a qualitative measure of correlation.

A correlation value always comes between -1 to 1. That is, the coefficient of correlation (denoted by r) between two variables cannot exceed unity and it always lies between -1 to 1. If r = 1, then the correlation is perfect and positive and if r = -1, then the correlation is perfect and negative.

In a graph we can look Mathematics, if the y variable tends to increase as x increases, then the correlation is called as positive or direct correlation. If all the values of the variables satisfy an equation exactly, we say that the variables are perfectly correlated or that there is a perfect correlation between them.

If all the points that are lying in the scatter diagram seem to lie near a single line, then the correlation is called as linear. A scatter plot measures the linear relationship between the variables x and y, but however, for nonlinear relationships between the variables, this scatter plot is not very suitable.

If y tend to decrease as x increases, the correlation is called as negative or inverse correlation. If all the points seem to lie near some curve, the correlation is called non linear. If there is no relationship indicated between the variables we say that there is no correlation between the variables, that is they are uncorrelated.

in short, in a scatter plot is a graph showing cause and effect of two variables and by plotting the points (x, y) on a rectangular coordinate system, we can find out the correlation between x and y, which can fall under any seven categories:

  1. Perfect positive Correlation, when r = 1
  2. High positive correlation, when r lies between 0.5 to 1
  3. Low positive Correlation, when r lies between 0.5 to 0
  4. No correlation, when r = 0
  5. Low negative correlation, when r lies between -0.5 to 0
  6. High negative correlation, when r lies between -0.5 to -1
  7. Perfect negative correlation, when r = -1

So, by looking at the scatter plot, we can find out either of the above 7 correlation between 2 variables, as how much the point is scattered around a line. For example, a low positive correlation indicates too much scatter- ness of points in an upward direction.

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