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Python Radars manufactures radar systems, It has just completed the manufacture of its first newly designed system, RS-32. Manufacturing data for the RS-32 follow: (Click icon to view more data) Read the Requirement 1. Calculate the total variable costs of producing 2, 3, and 4 units assuming that Python Radars uses an 85% incremental unit-time leaming model as a basis for predicting direct manufacturing labor-hours. Begin by calculating the cumulative total time in labor-hours using the incremental unit-time leaming model. (Round the individual unit time for Xth unit to the nearest whole number.) Requirements 1. Calculate the total variable costs of producing 2,3 , and 4 units assuming that Python Radal uses an 85% incremental unit-time learning model as a basis for predicting direct manufacturi labor-hours. 2. Compare the cost predictions from requirement 1 (incremental unit-time learning model) wit the cost predictions of producing 2 and 4 units based on a cumulative average-time leaming Data table model. Why are the predictions different? How should Python Radars decide which model it should use? Cumulative average-time learning model's cumulative average time per unit and cumulative total time and total variable cost predictions of producing 2 and 4 units

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