curves are used in production operations to estimate the time required to complete a repetitive task as an operator gains experience. Suppose a production manager has compiled 30 time values (in minutes) for a particular operator as she progressed down the learning curve during the first 100 units. A portion of this data is shown in the acco
Learning curves are used in production operations to estimate the time required to complete a repetitive task as an operator gains experience. Suppose a production manager has compiled 30 time values (in minutes) for a particular operator as she progressed down the learning curve during the first 100 units. A portion of this data is shown in the accompanying table.
| Time_Per_Unit | Unit_Number |
| 18.50 | 1 |
| 17.70 | 5 |
| 12.60 | 9 |
| 11.40 | 10 |
| 10.10 | 19 |
| 8.30 | 20 |
| 9.20 | 22 |
| 8.90 | 29 |
| 8.10 | 28 |
| 8.60 | 33 |
| 8.00 | 35 |
| 7.50 | 38 |
| 6.40 | 43 |
| 6.90 | 44 |
| 7.20 | 49 |
| 6.90 | 52 |
| 7.30 | 54 |
| 6.40 | 56 |
| 6.90 | 61 |
| 6.20 | 66 |
| 7.00 | 65 |
| 6.70 | 68 |
| 6.30 | 73 |
| 6.10 | 76 |
| 6.20 | 82 |
| 6.00 | 88 |
| 6.30 | 90 |
| 5.90 | 90 |
| 5.70 | 95 |
| 5.10 | 98 |
b. Estimate the simple linear regression model and the logarithmic regression model with time per unit as the response variable and unit number as the predictor variable. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)
Time = 12.48 + -0.09 unit
Time = ? + ? ln(unit)
c. Based on R2, use the best-fitting model to predict the time that was required for the operator to build Unit 67. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)
Times = ? minutes
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