What you'll get
- 4+ Hours
- 1 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Covers the theoretical foundations of logistic regression analysis.
- Provides practical implementation techniques using SAS Stat software.
- Guides learners in exploring and interpreting datasets for logistic regression.
- Teaches handling of missing values and categorical inputs in regression models.
- Explains variable clustering methods to identify related predictor variables.
- Covers subset selection techniques for optimizing logistic regression models.
- Offers strategies for effectively interpreting and analyzing model outputs.
- Demonstrates how to create logit plots to visualize relationships between variables.
- Highlights best practices for model evaluation and validation.
- Applies logistic regression analysis to real-world datasets for data-driven decision-making.
- Provides detailed insights into regression analysis, explaining key concepts and benefits of logistic regression.
- Enables learners to accurately interpret SAS-generated logistic regression outputs.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Logistic Regression Project using SAS Stat | 4h 26m | ✔ | View Curriculum |
Description
This course provides participants with the skills to master logistic regression analysis in SAS. The training begins with a detailed introduction to logistic regression concepts, with emphasis on practical applications. Learners will work with real-world datasets, such as an insurance dataset, to explore and prepare data effectively for analysis.
Participants will gain hands-on experience in conducting logistic regression analysis, including:
- Handling missing values and encoding categorical variables
- Interpreting model outputs to derive actionable insights
- Performing variable clustering to identify related groups of variables and streamline model building
- Applying subset selection methods to determine the most influential predictors for accurate outcome prediction
The course combines theory with practical exercises, ensuring learners build confidence in applying logistic regression techniques to real-world projects. Participants gain access to extensive resources and expert guidance to strengthen their understanding and analytical skills. By the end of the course, learners will be proficient in using SAS/STAT for logistic regression analysis, enabling data-driven decision-making and improving outcomes across research and business applications.
Requirements
- Basic familiarity with SAS is recommended
- No prior advanced skills are required to enroll
Target Audience
- Researchers, Data Miners, Epidemiologists, Environmental Scientists.
- Anyone interested in data modeling and probability estimation.
