This course covers a range of introductory statistical topics and uses SAS software to carry out analysis. Emphasis will be placed on the interpretation of the results. It covers the skills required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models). Ready-to-use procedures handle a wide range of statistical techniques including simple descriptive statistics, data visualization, analysis of variance, regression, categorical data analysis, multivariate analysis, cluster analysis, and non parametric analysis are part of this program
Learn how to
Generate descriptive statistics and explore data with graphs
Perform analysis of variance
Perform linear regression and assess the assumptions
Use diagnostic statistics to identify potential outliers in multiple regression
Use chi-square statistics to detect associations among categorical variables
Fit a multiple logistic regression model.
Learn how to
Define a SAS Enterprise Miner project and explore data graphically
Modify data for better analysis results
Build and understand predictive models such as decision trees and regression models
Compare and explain complex models
Generate and use score code
Apply association and sequence discovery to transaction data.
To get started in SAS for free we recommend you look at these online tutorials – there are nearly 200 and are suitable for people who are new to SAS, and then from there review the appropriate learning path to start your learning journey.
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