e) Mode: What is the mode for "level of education"? What is the mode for "interest inpolitics"?f) Median: What is the median for "level of education"? What is the median for "interestin politics"?g) Mean: What is the mean for "level of education"? What is the mean for "interest inpolitics"?h) Relationship between IV and DV: Using the table, how would you characterize therelationship between the independent and dependent variables? Does it appear to be apositive relationship, a negative relationship or no clear relationship between thevariables? Describe how you are reaching your conclusions (How would you convincesomeone to accept your assessment of the data?) INTERESTIN POLITICSVery HighHighMediumLowVery LowTotalsGrade School High School College3143612253741LEVEL OF EDUCATION1182643323715240342116147Totals53781029094417

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Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015

1st Edition

ISBN:9781680331141

Author:HOUGHTON MIFFLIN HARCOURT

Publisher:HOUGHTON MIFFLIN HARCOURT

Chapter11: Data Analysis And Displays

Section11.5: Choosing A Data Display

Problem 19E

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NORTH–SOUTH AIRLINE CASENorthern Airline DataAirframe CostEngine CostAverage AgeYearper Aircraftper Aircraft(Hours)200151.8043.496,512200254.9238.588,404200369.7051.4811,077200468.9058.7211,717200563.7245.4713,2752006 84.7350.2615,215200778.7479.6018,390Southeast Airline DataAirframe CostEngine CostAverage AgeYearPer Aircraftper Aircraft(Hours)200113.2918.865,107200225.1531.558,145200332.1840.437,360200431.7822.105,773200525.3419.697,150200632.7832.589,364200735.5638.078,2591. Develop Regression equations for each cost category as dependent variables and average age as independent variables. Do this for each Airline. Look at graphs produced by QM2. From the regression results, what would you conclude about a) airframe vs engine costs for each airlineb) comparing airlines as to airframe costsc) comparing airlines as to engine costsd) Provide a brief summary report of your comparisons
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Weight City MPG 3968 20 3583 22 3470 22 3527 23 3990 18 4724 17 3692 21 3315 22 3616 20 5527 14 3719 16 3097 26 3800 19 3532 25 2269 31 5674 15 3402 20 4029 19 3996 19 3242 23 2434 31 2575 29 2960 27 3618 15 4054 19 3192 24 3305 23 3605 19 4240 15 3933 18 3633 19 3790 17 3477 20 3258 21 4685 17 2776 25 2615 24 3186 21 5137 13 3461 21 4233 16 4178 18 4702 17 3713 22 5794 14 2306 28 3194 26 3428 22 4894 12 4751 17 2605 29 3296 25 5267 13 2789 25 3570 19 4011 18 2363 27 4398 15 2806 25 2127 36 2665 27 3419 24 3427 24 3280 25 5765 13 3465 24 2295 30 3038 22 3070 25 4711 17 3230 24 3528 21 4667 16 SUMMARY OUTPUT Regression Statistics Multiple R 0.894328844 R Square 0.799824082 Adjusted R Square 0.797004703 Standard Error 2.238112689…
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