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Predicting bed census with multiple regression model

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To help schedule staffing and 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 30 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 error sum of squares (SSE) associated with the model is 60.39 and the corresponding regression sum of squares (SSR) is 9.41. Using a significance level of .10, 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.

I need help finding the value of the test statistic and p-value. Please include a spreadsheet to input numbers and figure it in the future. Thanks.

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The solution predicts bed census with multiple regression models.

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Hypothesis: H0: None of the independent variables in the model provides useful information for predicting daily bed census, vs.
HA: At least one of the independent variables in the model provides useful information ...

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