Business > CASE STUDY > Assignment 3 Unit 7.docx PREDICTING AN OUTCOME USING REGRESSION MODELS (All)

Assignment 3 Unit 7.docx PREDICTING AN OUTCOME USING REGRESSION MODELS

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Assignment 3 Unit 7.docx PREDICTING AN OUTCOME USING REGRESSION MODELS 1 MHA5017 Predicting an Outcome Using Regression Models Capella University Data Analysis for Health ...

Assignment 3 Unit 7.docx PREDICTING AN OUTCOME USING REGRESSION MODELS 1 MHA5017 Predicting an Outcome Using Regression Models Capella University Data Analysis for Health Care Decisions MHA5017 Predicting an Outcome Using Regression Models Multiple regression analysis is a way for us to understand more about the relationship between several independent or predictor variables and a dependent or criterion variable (Kros & Rosenthal, 2016). It also provides improvement of precision for estimation and prediction. In this assignment, hospital administration needs to a make a decision on the amount of reimbursement required to cover expected costs for next year. Based off the results of the multiple regression analysis, a true statistical significance will help quantify whether a result is likely due to chance or to some factor of interest (Gallo, 2016). The regression model will also interpret the R square that takes into consideration the three independent variables of age, risk, and satisfaction. These three independent variables will help explain the cost variable by understanding if there is a relationship between the independent and independent variables. With this analysis, the hospital administration will be able to predict the amount of reimbursement needed to cover cost. Interpret p-value and beta value This model overall is significant because the p-value is 0.0 which is less than 0.05. A significant result would be a p-value less than 0.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .. .. . . . . . . . . . . . . . . . . . .. . . . .

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