Juan Valdez trades in his old donkeys for two new llamas in order to transport his mountain grown coffee to the marketplace

Llamas make excellent pack animals and are surefooted, so I should be able to spend more time harvesting and less time wrangling animals, Juan thought to himself as he led the two back to his mountain farm. Much to his dismay, the first time he tried to strap the bags of coffee beans to his new llamas they resisted by running away and when he got close, they spit copiously. However, he was persistent and methodical, and he noticed that things went a little better each day. The time it took to get the llamas loaded up is summarized in the table.

Day Time (min) Day Time (min)
1 140 5 84
2 116 6 79
3 100 7 79
4 93 8 76

What learning rate is evident from the data?
How long will it take to load up the llamas next month (on the 30th attempt) if the same learning pattern continues?


The data were generated using an 80% learning curve plus an error term, which was generated by the function RAND()∗5, resulting in a mean of 2.5 and a standard deviation of 1.4. To determine the learning effect on display, the student might choose some output-doubling observations to make the comparison: Days 1 & 2 yields an estimate of 116/140= .825; days 2 & 4 an estimate of 93/116=.801; and days 4 & 8 an estimate of 76/93=.817. Moving forward with a learning effect of 81%
T30 = 140 × 30
T30 = 140 × 30-.3041
T30 = 140 × .3555875
T30 = 49.78 minutes

Juan is still trying to determine whether he or the llamas contribute more to the learning effect, but that's another question for another test bank.

Business

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