Use the Excel function COVARIANCE.S to compute the sample covariance between number of children and years of schooling. The sample covariance between number of children and years of schooling is . (Note: The COVAR function in Excel versions 7.0 and earlier returns the population covariance, rather than the sample covariance. To convert a population covariance to a sample covariance, you need to multiply the population covariance by n/(n-1) to obtain the sample covariance.) Given this value of the sample covariance, you know that the sample correlation coefficient between number of children and years of schooling will be Suppose, instead of measuring years of schooling in years, you measured it in months. Then, the absolute value of the sample covariance between number of children and years of schooling would and the absolute value of the sample correlation coefficient would Use the Excel function CORREL to compute the sample correlation coefficient between number of children and income (in $1,000s) The sample correlation coefficient between number of children and income (in $1,000s) is r X 75 2 File Home i Protected View F5 1 ID 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 144 A adult demographicsl (3) [Protected View)- Microsoft Excel non-commercial use Insert Page Layout Formulas Data Review View DYMO Label Acrobat This file originated from an Internet location and might be unsafe. Click for more details. Enable Editing f 41-50 C D E F B gender G 1 K number of children age (years age category marital status married 1001 female 2 39.5 31-40 education years of schooling 2 yr college 1002 male married 1 62.5 61 or older 1003 male married 4 H income (income category 116.4 $100K $149K 77.5 $60K $79K 95.5 $80K-$99K 129.9 $100K $149K 128.0 $100K $149K 188.7>$150K 25.6 26-30 1004 male 41.341-50 never married. widowed 1005 female 1006 female 44.2 41-50 64.3 61 or older 54.0 51-60 never married married divorced 1007 female 17 17 19 18. 15 13 13 14 10 14 17 21 4 yr college post-gradua 4 yr college 2 yr college high school high school 2 yr college less than hi high school 4 yr college post-gradua 1008 female 1009 female married. 1010 male. 40.3 41-50 58.7 51-60 29.1 26-30 45.8 41-50 46.2 41 50 1011 male 1012 male 68.7 $60K-$79K 39.6 $20K - $39K 97.6 $80K-$99K 416 $40K-$59K 259.8 $150K 174.1>$150K 162.3>$150K 132.2 $100K-$149K 61.1 $60K $79K 71.2 $60K $79K 111.5 $100K $149K 1013 male 43.2 41 50 4 yr college married married separated divorced divorced married married married 19 1014 female. 40.6 41 50 1015 female 35.0 31-40 1016 male 39.0 31-40 1017 female 32.2 31-40 4 yr college less than hi some colle post-gradua some colleg post-gradua high school 27.6 26-30 1018 male, 69.0 $60K $79K 228.3 $150K 55.2 51-60 1019 male. 41.9 41-50 1020 male married divorced never married divorced separated married 2 yr college 1021 male 39.6 31-40 32.4 31-40 1022 female 45.9 41-50 1023 male 81.5 $80K-$99K 101.5 $100K $149K 68.8 $60K-$79K 102.3 $100K $149K 158.7>$150K 24.5 $20K $39K 70.4 $60K $79K 54.2 $40K-$59K 47.6 41-50 1024 female married widowed 31.2 31-40 4 yr college 4 yr college post-gradua less than hi some colle some colleg * 1025 male 43.1 41-50 1026 male never married married 32.8 31-407 1027 female adult demographics1 X Ready W 0 2 0 3 2 0 2 1 2 0 3 6 2 2 0 1 1 10 5 2 3 3 0 4 20 11 15 20 15 22 14 17 16 17 18 13 14 16 $12 L prisc M N O 100% - - 14 CHEM P 9:33 9/8/2 RESICI adult demographics] (3) DYMO Label File Home Insert Page Layout [Protected View) Microsoft Excel non-commercial use Acrobat Formulas Data Review View i Protected View This file originated from an Internet location and might be unsafe. Click for more details. Enable Editing F55 fix A B D E F G H J 28 1027 female 4 32.8 31-40 married divorced 29 1028 female 1 some colleg some colleg high school 2 54.2 $40K-$59K 122.3 $100K-$149K 101.9 $100K-$149K 18.6