A Multiple Regression Analysis Is Used To Determine The

A multiple regression analysis is used to determine the relationship or association between independent variables (IVs), also known as predictor variables, and a dependent variable (DV) (Sen Srivastava, 2012). The purpose of the report is to summarize and analyze the Virginia Hospitals data from 2005 to determine run a multiple regression model against multiple predictor variables and determine statistical significance between the various hospital variables (i.e. independent variables) and the Total Operating Expense (TOE). A multiple linear regression was calculated to predict the DV (i.e.Total Operating Expense_05) based on the IVs (i.e. Staffed beds_05, Medicare Days_05, Medicaid Days_05, Total Surgeries_05, RN FTE_05, Occupancy,†¦show more content†¦For the Staffed beds_05, the hypothesis is that the number of staffed beds has a positive association (ÃŽ ²1 0) with TOE; staffed beds require regular care and maintenance, so an increase in staffed bed increases TOE (Vil la Kane, 2013). For the Medicare Days_05, the hypothesis is that Medicare days have a negative association (ÃŽ ²2 0) with TOE; Medicare days affect the hospital s revenue based on Medicare coverage, and so, an increase in Medicare days decreases TOE (Villa Kane, 2013). For the Medicaid Days_05, the hypothesis is that Medicaid days have a negative association (ÃŽ ²3 0) with TOE because Medicaid days increases the hospital s expenses/bad debt; therefore an increase in Medicaid days decreases TOE (Villa Kane, 2013). For the Total Surgeries_05, the hypothesis is that total surgeries have a positive association (ÃŽ ²4 0) with TOE as surgical procedures incur costs with the use of specific/specialized drugs and equipment and post-operative care; therefore, as total surgeries increase, TOE increases (Fay, 2016). For the RN FTE_05, the hypothesis is that RN FTE has a positive association (ÃŽ ²5 0) with TOE as increasing the level of nurse staffing, especially full-time (FTE) regi stered nurses (RN), increases TOE due to the salary payment (Investopedia, 2014). For the Occupancy, the hypothesis is that occupancy has a positive association (ÃŽ ²6 0) withShow MoreRelatedIv.Proposed Model. This Section Introduced The Proposed1333 Words   |  6 Pagesfactors in agile software projects. - The proposed model uses multiple linear regressions to determine critical failure factors in agile software projects. - The proposed model uses fuzzy logic for predicting failure of agile software projects. Figure4. 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