Vol. 8, No. 9

September 2006

PQ Systems
 
Contents

Quality Gamebox article

Quality Quiz: With a video!

Six Sigma

Data in everyday life

Bytes and pieces

FYI: Current releases

 

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Software

 

   

Quality Quiz from Professor Cleary

Congratulations:
"B" is correct.

Click here for a more complete video explanation

Kohl is too quick to comment without considering the real meaning of the statistic, and is wrong about Coefficient of Determination's implications.

Coefficient of Determination is a statistic that indicates the percent of variation in Y (the dependent variable) that can be explained by X (the independent variable). Examining the scatter diagram below, one can see that the Coefficient of Determination is equal to 1. In other words, X explains 100% of the variation in Y.

In this case, X is a perfect predictor of Y. Knowing what X's value is, and putting that value into the regression equation (e.g., X = 2), Y = 0 +2X, or Y = 0+2(2), you will derive 4, the predicted value of Y, given an X of 2.

Looking again at Kohl's regression analysis:

A relationship between X and Y is clear from this chart.

Finally, in an example where X has little or nothing to do with Y:

It is clear that there is no close pattern. Observations appear to be randomly placed. There continues to be a regression line (Y = 6.13 + 0.02 X), that offers the best fit, even if that fit is not especially good.

Recall that last month we learned how to test the goodness of fit by using the t statistic to examine the hypothesis that B = 0. If you were to go through the four steps, what do you think the conclusion would be?

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