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Ch 13 #2 - X = Covariance X,Y =*Answers may differ slightly...

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Chapter 13 #2. EDUC CHILDS ( X -) ( X -) 2 ( Y -) ( Y -) 2 ( X -) ( Y -) 16 0 3.44 11.83 -2.04 4.16 -7.02 12 1 -0.56 0.31 -1.04 1.08 0.58 12 3 -0.56 0.31 0.96 0.92 -0.54 6 6 -6.56 43.03 3.96 15.68 -25.98 14 2 1.44 2.07 -0.04 0.00 -0.06 14 2 1.44 2.07 -0.04 0.00 -0.06 16 2 3.44 11.83 -0.04 0.00 -0.14 12 2 -0.56 0.31 -0.04 0.00 0.02 17 2 4.44 19.71 -0.04 0.00 -0.18 12 3 -0.56 0.31 0.96 0.92 -0.54 14 4 1.44 2.07 1.96 3.84 2.82 13 0 0.44 0.19 -2.04 4.16 -0.90 12 1 -0.56 0.31 -1.04 1.08 0.58 12 2 -0.56 0.31 -0.04 0.00 0.02 12 3 -0.56 0.31 0.96 0.92 -0.54 11 1 -1.56 2.43 -1.04 1.08 1.62 12 2 -0.56 0.31 -0.04 0.00 0.02 11 2 -1.56 2.43 -0.04 0.00 0.06 12 0 -0.56 0.31 -2.04 4.16 1.14 12 2 -0.56 0.31 -0.04 0.00 0.02 12 3 -0.56 0.31 0.96 0.92 -0.54 12 4 -0.56 0.31 1.96 3.84 -1.10 12 1 -0.56 0.31 -1.04 1.08 0.58 14 0 1.44 2.07 -2.04 4.16 -2.94 12 3 -0.56 0.31 0.96 0.92 -0.54 Σ X =314 Σ Y =51 Σ =0.0* Σ =104.07 Σ =0.0* Σ =48.92 Σ =-33.62 Mean X = Mean Y = Variance ( Y ) = Standard deviation ( Y ) =
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Variance ( X ) = Standard deviation (
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Unformatted text preview: X ) = Covariance ( X,Y ) = *Answers may differ slightly due to rounding. a. The Correlation coefficient is –0.47. This does support the hypothesis, since greater education is associated with fewer children. b. Ŷ = 6.10 - .323 X c. The predicted number of children is CHILDS = Ŷ = 6.10 - .323(16) =0 .93 d. Yes, a respondent with 11 or 12 years of education has only 1 child. The fact that this person does not have 16 years of education is not an indication that the equation is incorrect. We don’t expect that a linear relationship will fit the data perfectly; in other words, there is always error in predictions....
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