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1. For each pair of variables, calculate the q-correlation, using the formula: , where 1. For each pair of variables, calculate the q-correlation, using the formula: , where = number of data points in the upper-right quadrant = number of data points in the lower-left quadrant = number of data points in the lower-right quadrant = number of data points in the upper-left quadrant n = n1 + n2 + n3 + n4

Q: What is a Q correlation?

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Suppose the scatter plot is of a variable X on the horizontal scale and Y on the vertical scale.Find the approximate middle of the x values and call it p.Find the approximate middle of the y values and call it q.Draw horizontal and vertical lines through the point with coordinates (p, q).If you know about quadrants, skip this paragraph. The two lines through the point (p,q) divide up the plane into 4 quadrants. Quadrant I is top right. Quadrant II is top left. Quadrant III is bottom left. Quadrant IV is bottom right.If the scatter plot is mostly in quadrants I and III the correlation is positive. If mostly in quadrants II and IV the correlation is negative. Otherwise the correlation is small.Remember, though, that 0 correlation does not mean no relation. y = x2 will have 0 correlation but it is a perfectly well defined relationship!Suppose the scatter plot is of a variable X on the horizontal scale and Y on the vertical scale.Find the approximate middle of the x values and call it p.Find the approximate middle of the y values and call it q.Draw horizontal and vertical lines through the point with coordinates (p, q).If you know about quadrants, skip this paragraph. The two lines through the point (p,q) divide up the plane into 4 quadrants. Quadrant I is top right. Quadrant II is top left. Quadrant III is bottom left. Quadrant IV is bottom right.If the scatter plot is mostly in quadrants I and III the correlation is positive. If mostly in quadrants II and IV the correlation is negative. Otherwise the correlation is small.Remember, though, that 0 correlation does not mean no relation. y = x2 will have 0 correlation but it is a perfectly well defined relationship!Suppose the scatter plot is of a variable X on the horizontal scale and Y on the vertical scale.Find the approximate middle of the x values and call it p.Find the approximate middle of the y values and call it q.Draw horizontal and vertical lines through the point with coordinates (p, q).If you know about quadrants, skip this paragraph. The two lines through the point (p,q) divide up the plane into 4 quadrants. Quadrant I is top right. Quadrant II is top left. Quadrant III is bottom left. Quadrant IV is bottom right.If the scatter plot is mostly in quadrants I and III the correlation is positive. If mostly in quadrants II and IV the correlation is negative. Otherwise the correlation is small.Remember, though, that 0 correlation does not mean no relation. y = x2 will have 0 correlation but it is a perfectly well defined relationship!Suppose the scatter plot is of a variable X on the horizontal scale and Y on the vertical scale.Find the approximate middle of the x values and call it p.Find the approximate middle of the y values and call it q.Draw horizontal and vertical lines through the point with coordinates (p, q).If you know about quadrants, skip this paragraph. The two lines through the point (p,q) divide up the plane into 4 quadrants. Quadrant I is top right. Quadrant II is top left. Quadrant III is bottom left. Quadrant IV is bottom right.If the scatter plot is mostly in quadrants I and III the correlation is positive. If mostly in quadrants II and IV the correlation is negative. Otherwise the correlation is small.Remember, though, that 0 correlation does not mean no relation. y = x2 will have 0 correlation but it is a perfectly well defined relationship!

Auto correlation is the correlation of one signal with itself. Cross correlation is the correlation of one signal with a different signal.

Once you have figured out all the quadrants and their respective values, use: q=a+b-c-d/a+b+c+d For example if: a=6 b=3 c=4 d=2 q=6+3-4-2/6+3+4+2 =3/15

positive correlation-negative correlation and no correlation

No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).

The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).

If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.

No.

Indentation rhymes with correlation

Evidence that there is no correlation.

No, The correlation can not be over 1. An example of a strong correlation would be .99