This Course is designed for students at the Beginner level.
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For SAS software users looking to delve into statistical analysis, this introductory course is tailored to equip you with the foundational skills necessary for leveraging SAS/STAT software effectively. With a focus on t-tests, ANOVA, linear regression, and an introduction to logistic regression, this course is an essential stepping stone for users in statistical analysis and modeling. Designed for statisticians, researchers, and business analysts, it provides a comprehensive overview of key statistical concepts and techniques.
Participants will learn to generate descriptive statistics, visualize data with graphs, and perform inferential analyses using SAS procedures like UNIVARIATE and TTEST. Explore analysis of variance (ANOVA) to test group differences and apply multiple comparison techniques for deeper insights. Master the art of fitting and interpreting linear regression models, assessing assumptions, and diagnosing potential outliers using statistical tools.
The course also introduces chi-square statistics for analyzing associations between categorical variables and progresses to logistic regression. Gain hands-on experience fitting logistic regression models and scoring new data for predictive analysis. Advanced modeling techniques such as PROC GLMSELECT enable participants to automate model selection, investigate residuals, and address issues like collinearity for more robust analyses.
Prerequisites include a basic understanding of statistics, hypothesis testing, and SAS programming. Those looking for advanced topics can pursue follow-up courses on ANOVA, regression, and predictive modeling for more specialized knowledge.
By the end of this course, attendees will be equipped with the skills to perform data analysis, model building, and prediction using SAS/STAT. Whether you’re an academic researcher or a business analyst, this course provides practical insights into applying statistical methodologies to real-world problems.
