The Statistical Business Specialist qualification is appropriate for professionals who fix business problems by doing statistical Analysis and predictive Model using SAS/STAT program.
SAS statistical program allows companies to understand from, implement, and improve on details acquired from wide stores of details. The SAS Certified Statistical Business Specialist Using SAS 9: Regression and Model qualification is designed for SAS professionals that use SAS/STAT program to execute and understand complex statistical details analysis. The qualification specializes in directly line and logistic regression methods used to make predictive styles. A thorough understanding of essential analysis is also important.
SAS Institution SAS Statistical Business Analysis SAS9: Regression and Model
The recommended preparing for the SAS Statistical Business Analysis Using SAS 9: Regression and Model evaluation are based on Analysis 1: Launch to ANOVA, Regression, and Logistic Regression and Predictive Model Using Logistic Regression applications. While no evaluation problems will be drawn the same from the applications or course exercises, these applications will provide candidates with a platform from which to implement the capabilities and details necessary for the evaluation. Experience is an essential factor to becoming a SAS Certified Professional.
Statistics 1: Launch to ANOVA, Regression, and Logistic Regression
This starting course is for SAS application customers who execute statistical Analysis using SAS/STAT application. The concentrate is on t assessments, ANOVA, and directly line regression, and has a brief guide to logistic regression. This course (or comparative knowledge) is a precondition to many of the programs in the statistical analysis program. A more innovative therapy of ANOVA and regression happens in the Analysis 2: ANOVA and Regression course. A more innovative therapy of logistic regression happens in the Specific Information Analysis Using Logistic Regression course and the Predictive Modeling Using Logistic Regression course.
Learn how to generate illustrative statistics and discover data with charts, perform analysis of difference and implement several evaluation methods, perform directly line regression and evaluate the presumptions, use regression model choice methods to aid in the choice of forecaster factors in several regression, use analytic statistics to evaluate statistical presumptions and recognize potential outliers in several regression, use chi-square statistics to recognize organizations among categorical factors and fit a several logistic regression model.
Predictive Modeling Using Logistic Regression
This course protects predictive modeling using SAS/STAT application with concentrate on the LOGISTIC process. This course also talks about choosing factors, evaluating styles, dealing with losing principles and using performance methods for large data places.
Learn how to use logistic regression to model an person’s actions as a operate of known information, create impact plots and possibilities rate plots using ODS Statistical Model, handle losing data principles, tackle multi co linearity in your predictors and assess model performance and evaluate styles.