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ReviewMar02

# ReviewMar02 - Manpower Data Linear Regression Review...

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Manpower Data Linear Regression Review Tutorial for Stat 331 Adrian Waddell University of Waterloo February 2, 2010 Adrian Waddell (University of Waterloo) Applied Linear Models February 2, 2010 1 / 13

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Manpower Data Manpower Data Consider the hospital manpower data collected from 17 US Naval hospitals at various sites around the world. The explanatory variables are workload variables, i.e., items that result in the need for manpower in a hospital installation. A brief description of the variables is given as follows: y Monthly man-hours x 1 Average daily patient load x 2 Monthly X-ray exposures x 3 Monthly occupied bed days x 4 Eligible population in the area/1000 x 5 Average length of patients’ stay in days Adrian Waddell (University of Waterloo) Applied Linear Models February 2, 2010 2 / 13
Manpower Data Model We want to ﬁt the model y = β 0 + β 1 x 1 + β 2 x 2 + β 3 x 3 + β 4 x 4 + β 5 x 5 + ± where ± N ( 0, σ 2 ) independently. Fitted model is ˆ y = ˆ β 0 + ˆ β 1 x 1 + ˆ β 2 x 2 + ˆ β 3 x 3 + ˆ β 4 x 4 + ˆ β 5 x 5 where ˆ β j are the least squares estimates. Adrian Waddell (University of Waterloo) Applied Linear Models February 2, 2010 3 / 13

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Manpower Data Parameter estimation Read data into R : 1 man < - read . table ( ’ manpower . txt ’ , header = TRUE, sep = ’ ; ’ ) Fit model 1 f i t < - lm ( y ˜ x1+x2+x3+x4+x5 , data =man) or do it yourself 1 X < - as . matrix ( cbind
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ReviewMar02 - Manpower Data Linear Regression Review...

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