Hack into SAS Statistical Business Analysis Certification | It Certification Online Course by Udemy

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Full coverage of the A00-240: Regression and Modeling: 5 practice exams!

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Hack into SAS Statistical Business Analysis Certification

COURSE ABSTRACTThis is an exam-based prep “course”, and the exam questions are specifically tailored for the certification: latest questions, and many case studies for coding practice! Each of the item is fully covered with several questions and any blind spot is avoided. You will have about 4-6 practice exams, in which you will have about 20 multiple choice questions. You will be fully prepared once you go through these practice exams. Save time and money by taking these practice exams. Let’s hack into the certification exam! The certificate requires the knowledge and experience in: Analysis of variance. Linear and logistic regression. Preparing inputs for predictive models. Measuring model performance. The proportion of each item is as follows: ANOVA – 10%Verify the assumptions of ANOVAAnalyze differences between population means using the GLM and TTEST proceduresPerform ANOVA post hoc test to evaluate treatment effectDetect and analyze interactions between factorsLinear Regression – 20%Fit a multiple linear regression model using the REG and GLM proceduresAnalyze the output of the REG, PLM, and GLM procedures for multiple linear regression modelsUse the REG or GLMSELECT procedure to perform model selectionAssess the validity of a given regression model through the use of diagnostic and residual analysisLogistic Regression – 25%Perform logistic regression with the LOGISTIC procedureOptimize model performance through input selectionInterpret the output of the LOGISTIC procedureScore new data sets using the LOGISTIC and PLM proceduresPrepare Inputs for Predictive Model Performance – 20%Identify the potential challenges when preparing input data for a modelUse the DATA step to manipulate data with loops, arrays, conditional statements and functionsImprove the predictive power of categorical inputsScreen variables for irrelevance and non-linear association using the CORR procedureScreen variables for non-linearity using empirical logit plotsMeasure Model Performance – 25%Apply the principles of honest assessment to model performance measurementAssess classifier performance using the confusion matrixModel selection and validation using training and validation dataCreate and interpret graphs (ROC, lift, and gains charts) for model comparison and selectionEstablish effective decision cut-off values for scoringThis exam is administered by SAS and Pearson VUE.60 scored multiple-choice and short-answer questions.(Must achieve score of 68 percent correct to pass)In addition to the 60 scored items, there may be up to five unscored items. Two hours to complete exam. Use exam ID A00-240; required when registering with Pearson VUE.

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