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Understanding the Correlation Coefficient, r Goal: To understand that r, the correlation coefficient, is most useful in describing the direction of a linear relationship while r2, the coefficient of determination, is most useful in describing the strength of a linear model. Since r2 is the square of r, r2 and r must be related. Does r tell us something about how well a linear model fits data, i.e. the strength of a linear model? Yes! However r2 is a better measure of the strength of a linear model. Let’s see how r indicates the direction of the linear relationship. Correlation Definition of Correlation The correlation, usually written r, measures the strength and direction of the linear relationship between two quantitative variables. 1 1 x x yi y r n 1 is sy x 1. Focus on r as an indicator of direction. Here is a special case: a. By hand, draw an estimate of your LSR line. (1,4) (3,4) b. Estimate r without calculator (1,2) (3,2) c. Estimate the slope of the LSR line . d. Check your answers with the calculator. Use lists L1 and L2 . e. Remembering that we want to focus on the direction, why is r = 0? 2. a. What is different about the data below? 1 after Basic Practice of Statistics, p. 98 Understanding the Correlation Coefficient, r (1,3 .5 ) b. Without using your calculator, decide if r is (3,3 .5 ) different than in part 1? Why or why not? (1,2 .5 ) (3,2 .5 ) c. Draw an estimate of your LSR line. d. Check your answers with the calculator. Understanding the Correlation Coefficient, r 3. Now let's look at a more typical set of data. Should r now be different than zero? Why? (3,5) a. Draw by hand an estimate of your LSR line. (1,4) b. Estimate r without calculator (3,3) (1,2) c. Estimate the slope of the LSR line d. Check with the calculator and, if necessary, alter your answers. 4. a. What is different about data below? (3,4.5) b. Without using your calculator, decide if the slope of the LSR line change from #3 above? (1,3.5) (3,3.5) (1, 2.5) Understanding the Correlation Coefficient, r c. Without using your calculator, decide if r is different? Challenge: Specifically state what has changed in the formula for r found at the beginning of this investigation. Does it help in making this decision? Check with your teacher. d. Check your answers with the calculator. r= The slope of the LSR line = e. You should have determined that the slope of the LSR line is the same in part 3 and 4 while the value of r is closer to "1" in part 4. Which data appears to be better modeled by the LSR line, part 3 or part 4? So r must also indicate something about the strength of the model. However, as suggested, the strength is best represented by r2. Understanding the Correlation Coefficient, r 5. Challenge Question: In problem #1 you determined that the LSR line was the horizontal (3,4) (1,4) line y = 3. Is the vertical line x= 2 (shown to the right) just as good a candidate for the LSR line? Explain. [This problem was (1,2) (3,2) designed by Leah Temple, BB&N ‘98.] 6. Challenge Question. [This problem was designed by Graham Howarth, BB&N ‘98.] a. Without using your calculator, estimate the value of r for the LSR line for the data (1,6), (2,6), (3,6), (4,6). b. Check your answer with the calculator. Can you find a way to have your calculator plot these points? c. Explain why r is undefined. - end -

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correlation coefficient, X and Y, linear relationship, positive correlation, random variables, correlation matrix, Negative correlation, Pearson correlation coefficient, Pearson correlation, partial correlation

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posted: | 12/26/2010 |

language: | English |

pages: | 5 |

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