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Cost Modeling

# Cost Modeling - <= 1 Y2 0.45<= 1 Function Max...

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1 Ryan Grandin Cost Modeling: DO PC Estimated PC Error (Error)^2 Day 1 5045 2542 2589.22 47.22 2229.85 Day 2 6127 2812 3008.13 196.13 38468.44 Day 3 6360 2776 3098.34 322.34 103905.1 Day 4 6645 3164 3208.69 44.69 1996.76 Day 5 7220 4102 3431.3 -670.7 449831.87 Day 6 9537 4734 4328.37 -405.63 164538.98 Day 7 9895 4238 4466.97 228.97 52427.71 Day 8 10,175 4524 4575.38 51.38 2639.61 Day 9 10,334 4869 4636.94 -232.06 53853.54 Day 10 10,855 4421 4838.65 417.65 174430.9 sum: 1044322.76 a = 635.97 b = 0.39 Min: 1044322.7618 2 Charity Advertising Budget: City 1 City 2 Response parame 0.01 0 Population 750,000 600,000 Average donation p \$2.00 \$1.50 Yi 0.78 0.45 Xi 251.63 148.37 Variables: Xi = amount allocated to city i for advertising Yi = fraction of city i's population that donates Constraints: X1 + X2 400 <= 400 Y1 0.78

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Unformatted text preview: <= 1 Y2 0.45 <= 1 Function: Max \$1,571,400.70 A B C D E F G 1 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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 Charity Advertising Budget: City 1 City 2 Response parameter 0.01 Population 750,000 600,000 Average donation per donor \$2.00 \$1.50 Yi 0.78 0.45 Xi 251.63 148.37 Variables: Xi = amount allocated to city I for advertising Yi = fraction of city I's population that donates Constraints: X1 + X2 400 <= 400 Y1 0.78 <= 1 Y2 0.45 <= 1 Function: Max \$1,571,400.70 A B C D E 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24...
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