What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
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This course is part of SAS Statistical Business Analyst Professional Certificate
Instructor: Jordan Bakerman
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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.
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.
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.
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.
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.
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.
25 videos18 assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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Reviewed on Jan 25, 2021
Must have taken the prior Course. In the Specialization.
Reviewed on Feb 13, 2021
Great Study material & Ease of understanding of the concepts.
Reviewed on Jun 14, 2021
Thanks so much to our instructor, Jordan Bakerman for teaching this course!
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