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 requirements. Requirement 1. Calculate the total variable costs of producing 2, 3, and 4 units assuming that Python Radars uses an 85% incremental unit-time learning model as a basis for predicting di manufacturing labor-hours. Begin by calculating the cumulative total time in labor-hours using the incremental unit-time learning model. (Round the individual unit time for Xth unit to the nearest whole number.) Requirements learning model. Why are the predictions different? How should Python Radars decide which model it should use? Cumulative average-time leaming model's cumulative average time per unit and cumulative total time and total variable cost predictions of producing 2 and 4 units: 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 requirements. Requirement 1. Calculate the total variable costs of producing 2, 3, and 4 units assuming that Python Radars uses an 85% incremental unit-time learning model as a basis for predicting di manufacturing labor-hours. Begin by calculating the cumulative total time in labor-hours using the incremental unit-time learning model. (Round the individual unit time for Xth unit to the nearest whole number.) Requirements learning model. Why are the predictions different? How should Python Radars decide which model it should use? Cumulative average-time leaming model's cumulative average time per unit and cumulative total time and total variable cost predictions of producing 2 and 4 units