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{"id":228019,"date":"2022-05-30T11:41:57","date_gmt":"2022-05-30T11:41:57","guid":{"rendered":"https:\/\/qualityassignments.net\/?p=228019"},"modified":"2022-05-30T11:41:57","modified_gmt":"2022-05-30T11:41:57","slug":"assignment-1-spss-discriminant-analysiswhile-regression-analysis-evaluates-the-ability-of-multiple-predictor-variables-to-predict-values-on-a-single-continuous-variable-discriminant-analysis-evaluat","status":"publish","type":"post","link":"https:\/\/qualityassignments.net\/2022\/05\/30\/assignment-1-spss-discriminant-analysiswhile-regression-analysis-evaluates-the-ability-of-multiple-predictor-variables-to-predict-values-on-a-single-continuous-variable-discriminant-analysis-evaluat\/","title":{"rendered":"Assignment 1: SPSS Discriminant AnalysisWhile regression analysis evaluates the ability of multiple predictor variables to predict values on a single continuous variable, discriminant analysis evaluat"},"content":{"rendered":"
\n

\n
\n
\n Assignment 1: SPSS Discriminant Analysis
\n <\/b>
\n<\/b>\n<\/p>\n

\n While regression analysis evaluates the ability of multiple predictor variables to predict values on a single continuous variable, discriminant analysis evaluates the ability of multiple predictor variables to predict classification on a single categorical variable. Discriminant analysis can also be viewed as the reverse of a MANOVA: In MANOVA, the IVs are the groups and the DVs are the predictors. In DA, the IVs are the predictors and the DVs are the groups.\u00a0(In order to avoid semantic confusion, it\u2019s easier to refer to IVs as the predictors\u2014or discriminating variables\u2014and to DVs as the grouping variables.)\n <\/p>\n

\n The emphases of MANOVA and DA are different. While MANOVA seeks to find a linear combination of variables that will maximize the test statistic, DA is used to establish the linear combination of dependent variables that maximally discriminates among groups. DA is used to predict membership in naturally occurring groups and to determine if a combination of variables can reliably predict group membership. Several variables are included in a study to see which ones best contribute to the discrimination between groups.\n <\/p>\n

\n As with factor analysis, discriminant functions are identified through the analysis, but it remains for the researcher to provide a meaningful interpretation and labeling of these.\n <\/p>\n

\n Use the
\n
\n Discussion Area
\n <\/b>
\n to ask for help in completing the tasks from your classmates and the facilitator; likewise, offer your suggestions to those asking for help. Participating in this community of scholars will help you clarify processes, solve problems, and gain the immediate reinforcement you need to quickly solidify gains that you\u2019re making in working with multiple variables and advanced statistics.\n <\/p>\n

\n Open the Statistical Package for the Social Sciences (SPSS) data file created in
\n
\n M6: Assignment 1
\n <\/b>
\n . Use the following variables:\n <\/p>\n

\n Create a Grouping Criterion Variable: Using the continuous data for Number of Previous Hospitalizations, transform this into categorical data by assigning patients to different categorical groups. You will add a new variable to your data file, which indicates which group each case falls into. For example, use the descriptive statistics and frequency information for the number of hospitalizations to decide your cut-offs for scores to define each group and then to assign patients to a group such as Group 1 (lower number of hospitalizations), Group 2 (medium number of hospitalizations), and Group 3 (higher number of hospitalizations) or you may consider quartiles, a median split, and dividing by standard deviation units. Justify your method.\n <\/p>\n

\n Select five (or more, if justified) continuous variables to use as predictor variables for your analysis. Briefly justify your choices.\n <\/p>\n

\n Conduct a discriminant analysis of these data. Use the same methods and choices found in the textbook\u2019s sample study. Include tests for homogeneity of group variances.\n <\/p>\n

\n Save the SPSS file as R7034_M7_A1_LastName_FirstInitial.sav.\n <\/p>\n

\n Prepare a two- to three-page (plus Appendix for tables) response, which presents a summary report of the following information:\n <\/p>\n