This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.
Regression Modeling Fundamentals
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Regression Modeling Fundamentals
This course is part of SAS Statistical Business Analyst Professional Certificate
Instructor: Jordan Bakerman
7,767 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.7
(52 reviews)
Intermediate level
Some related experience required
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
33 assignments
Taught in English
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This course is part of the SAS Statistical Business Analyst Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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There are 5 modules in this course
In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.
What's included
2 videos5 readings
In this module you explore several tools for model selection. These tools help limit the number of candidate models so that you can choose an appropriate model that's based on your expertise and research priorities.
What's included
11 videos3 readings4 assignments
In this module you learn to verify the assumptions of the model and diagnose problems that you encounter in linear regression. You learn to examine residuals, identify outliers that are numerically distant from the bulk of the data, and identify influential observations that unduly affect the regression model. Finally, you learn to diagnose collinearity to avoid inflated standard errors and parameter instability in the model.
What's included
18 videos7 assignments
In this module you learn how to transition from inferential statistics to predictive modeling. Instead of using p-values, you learn about assessing models using honest assessment. After you choose the best performing model, you learn about ways to deploy the model to predict new data.
What's included
11 videos1 reading4 assignments
In this module you look for associations between predictors and a binary response using hypothesis tests. Then you build a logistic regression model and learn about how to characterize the relationship between the response and predictors. Finally, you learn how to use logistic regression to build a model, or classifier, to predict unknown cases.
What's included
25 videos18 assignments
Instructor
Instructor ratings
4.5 (11 ratings)Offered by
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Frequently asked questions
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