A hospital emergency room analyzed n17665 hourly observation

A hospital emergency room analyzed n=17,665 hourly observations on its average occupancy rates using six binary predictor variables representing days of the week and two binary predictors representing the 8 hour work shift (12AM-8AM, 8AM-4PM, 4PM-12AM) when the ER census was taken. The fitted regression equation was AvgOccupancy = 11.2+1.19 Mon-.187 Tue-.785Wed-.580 Thurs - .451 Fri - .267 Sat - 4.58 Shift1-1.65 Shift2 (R^2 = .094, R^2 Adj = .093)

1.Why did the analyst use only six binaries for days when there are 7 days in a week?

2. Why did the analyst use only two binaries for work shifts when there are actually 3?

3. Which day of the week is the busiest?

4. Which shift is the busiest?

5. Interpret the intercept term

6. Asses the regression\'s fit

Solution

In the multiple regression fitting, some independent variable are not appear in the model but R2 value is very low that means only 9% independent variables explaine through the model.

1. analyst use only six binaries for days use in the model this may be due to these variables are correlated with dependent variable and significant for given data.

2. In the data set there are three shifts but in the model analyst use only two shifts this may be these variables are not that much correlated with the dependent variables.

3. Monday day of the week is the busiest because these day coefficient is +sign so there is highly chance to +vely correlated with dependent variables.

5. model havining intercept value 11.2 with +ve sign. regression line is not passing througt origin. dependent variable having minimum value is 11.2.

6. AvgOccupancy = 11.2 + 1.19 Mon - 0.187 Tue - 0.785Wed - 0.580 Thurs - 0 .451 Fri - 0.267 Sat - 4.58 Shift1 - 1.65 Shift2 is the multiple regression model with R2 value 0.094.