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I have a process which goes as follows. Products are ordered, and they are created at two terminals. Terminal A makes, say, green widgets. Terminal B makes, say, blue widgets. A customer may order as many of any combination of green or blue widgets. Recorded is the time it takes the customer to receive his order and the contents of the order. What is unknown is the effect on customer receiving time of ordering any particular number of green and/or blue widgets.

I have a model:

Time = A + BBlue + CGreen + DGreenBlue + error

Let's say I know beforehand that it usually takes longer to make green widgets than it does to make blue ones. Since the process of creating green and blue widgets happens simultaneously, will the data and the model likely be able to reflect the effects of each process separately? Or is the model improperly specified, and if so, how else could it be modeled?

Or in other words, is the only way to get a good look at the effect of each one...is the only way to know that...is that to time them separately?

Some sample data:

(Time, Blue, Green) (30, 1, 0) (45, 0, 1) (45, 1, 1) ... (32, 1, 0) (47, 0, 1) (40, 1, 1) ... (28, 1, 0) (43, 0, 1) (50, 1, 1) ... (60, 2, 0) (87, 0, 2) (87, 1, 2) (88, 2, 2) (91, 3, 2) (121, 4, 2)

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  • $\begingroup$ I think your model should be fine as specified. $\endgroup$
    – mkt
    Commented Jul 16, 2017 at 19:21

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