Discussion:
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?
The null hypothesis
Te alternate hypothesis
The type of test statistics
The value of test statistics
The critical value at 0.05 level of significance
Can you conclude that at least one of the independent variables in the model provides useful information for predicting daily bed census