To help schedule staffing equipment needs, a large hospital uses a multiple regression model to predict its 'bed census' y, the number of beds occupied at the end of each day. Using hospital records from the most recent 28 days, a total of 3 independent variables are used to find the estimated regression model. Let B1, B2 and B3 denote the coefficients of the 3 variables in this model. A computer printout indicates that the total sum of squares (SST) associated with the model is 572.37 and the corresponding regression sum of squares (SSR) is 252.83. Using a significance level of .05, can you conclude that at least one of the independent variables in the model provides useful (i.e., statistically significant) information for predicting daily bed census?
Perform a one-tailed test. Then fill in the table below.
Carry your intermediate computations to at least three decimal places and round your answers as specified in the table.
The solution performs a f test of multiple regression models. A one-tailed test is preformed.