Predicting daily revenue from customer count

Question

A cafe models its daily revenue against the number of customers served: \widehat{	ext{revenue}} = 200 + 15 \cdot (	ext{customers}). What revenue does the model predict on a day with 30 customers?

Accepted Answer

Substitute the input, 30 customers, into the line: \widehat{	ext{revenue}} = 200 + 15 	imes 30 = 200 + 450 = 650 	ext{ dollars.} The intercept \200 is a baseline (perhaps pastry and drip-coffee sales that happen regardless), and the slope \15 is the average spend each customer adds. For 30 customers the model expects about \650 in revenue. Order of operations matters: multiply the slope by the input first, then add the intercept. Adding before multiplying would give the wrong answer. Takeaway. Prediction is plug-and-compute: multiply slope by input, then add the intercept; 200 + 15 	imes …

Predicting daily revenue from customer count

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