Wednesday, November 20, 2019
MGM600-0803B-02 Applied Managerial Decision-Making - Phase 3 Essay
MGM600-0803B-02 Applied Managerial Decision-Making - Phase 3 Discussion Board 2 - Essay Example ANOVA test is of two types, One-Factor ANOVA and Two-Factor ANOVA (with and without replication). In One-Factor ANOVA, Dependent Variable (numerical) may be affected by one independent variable (categorical). In Two-Factor ANOVA, Dependent Variable (numerical) may be affected by two independent variables (categorical). An ANOVA test is useful, when different data sets (more than two) need to be compared for similar distribution population (treatment. A t-test can also be used for comparison; however, it is limited to two samples. For more than two data sets, many t-test needs to be carried out sequentially that will increase statistical error due to accumulation. An ANOVA test lessons the statistical error due to analysis of entire data set at once and makes it more likely that a determination can be made in valid manner (Skrzypczak, 2006; Pieniazekon, A. 2007). Suppose 10 dayââ¬â¢s daily defect rates for automotive computer chips manufactured production data for four different plant locations were available. Now for this data ANOVA can be useful for determining whether the observed differences in the plantsââ¬â¢ sample mean defect rates merely due to random variation or the observed differences between the plantsââ¬â¢ defect rates too great to be attributed to chance. Here ANOVA hypothesis will be ââ¬Ëmean defects rates are same for at all four plants (H0)ââ¬â¢ and ââ¬Ëat least one mean differs from the others (H1)ââ¬â¢. The One-Factor ANOVA dependent variable will be defect rate and independent variable will be plant locations (Doane, & Seward, 2007). Suppose a hospital management needs to test whether a patientââ¬â¢s length of a stay (LOS) depends on the diagnostic-related group (DRG) code and the patientââ¬â¢s age group, so that resources and fixed costs are correctly allocated. Considering case of bone fracture, LOS is a dependent variable measured in hours and type of fracture (facial, radius or ulna, hip or femur, other lower extremity, all other) and
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