SAS Statistical Business Analyst

▪ descriptive statistics

▪ inferential statistics

▪ steps for conducting a hypothesis test

▪ basics of using your SAS software

▪ examining data distributions

▪ obtaining and interpreting sample statistics using the UNIVARIATE and MEANS procedures

▪ constructing confidence intervals

▪ examining data distributions graphically in the UNIVARIATE and SGPLOT procedures

▪ performing simple tests of hypothesis

▪ performing tests of differences between two group means using PROC TTEST

▪ performing one-way ANOVA with the GLM procedure

▪ performing post-hoc multiple comparisons tests in PROC GLM

▪ performing two-way ANOVA with and without interactions

▪ producing correlations with the CORR procedure

▪ fitting a simple linear regression model with the REG procedure

▪ understanding the concepts of multiple regression

▪ using automated model selection techniques in PROC REG to choose from among several candidate models

▪ interpreting models

▪ examining residuals

▪ investigating influential observations

▪ assessing collinearity

▪ producing frequency tables with the FREQ procedure

▪ examining tests for general and linear association using the FREQ procedure

▪ understanding exact tests

▪ understanding the concepts of logistic regression

▪ fitting univariate and multivariate logistic regression models using the LOGISTIC procedure

▪ business applications

▪ analytical challenges

▪ parameter estimation

▪ adjustments for oversampling

▪ missing values

▪ categorical inputs

▪ variable clustering

▪ variable screening

▪ subset selection

▪ ROC curves and Lift charts

▪ optimal cutoffs

▪ K-S statistic

▪ c statistic

▪ profit

▪ evaluating a series of models