Question 1081172: A management consultant is studying the factors affecting the amount of time that it takes system administrators to complete tasks. In particular, she is interested in predicting the amount of time (in minutes) that it will take administrators to complete tasks, based on a set of variables collected for the engagement. The independent variables include – the age of the administrator (“Age”), the number of months of administrative job experience (“Experience”), whether or not the administrator has taken a job training (“Training”), and the level of complexity of the task as rated on a scale from 1 to 5 (“Complexity”). The dependent variable of interest is the amount of time (in minutes) that it takes the administrator to complete the assignment (“Performance”). Data are collected on the performance of 250 randomly selected administrators, each of whom was assigned a task to complete.
The following regression model emerged using a training data, as a result of several rounds of modeling. Assume that all parameters appearing in the model are statistically significant at 0.05 level, that no multicollinearity was detected among the independent variables, and that the residual diagnostics did not show serious violations of underlying assumptions. In addition, assume that complexity grows in a linear fashion. Note, that in the validation set the variables that do not show up in the final regression equation are omitted.
By how many minutes does the performance time change on average when complexity goes up by 1, all else kept constant? Does it go up or down? Type your answer like this: "up/down by X minutes"
Answer by Boreal(15235)   (Show Source):
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