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SAS Statistical Business Analyst

Offered By: SAS via Coursera

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Statistics & Probability Courses Business Intelligence Courses Statistical Modeling Courses Hypothesis Testing Courses Predictive Modeling Courses Logistic Regression Courses

Course Description

Overview

This program is for those who want to enhance their predictive and statistical modeling skills to drive data-informed business outcomes. If modeling data for business outcomes is relevant in your job role or industry, this certificate is a valuable indication of your proficiency.

Syllabus

Course 1: Introduction to Statistical Analysis: Hypothesis Testing
- Offered by SAS. This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on ... Enroll for free.

Course 2: Regression Modeling Fundamentals
- Offered by SAS. This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on ... Enroll for free.

Course 3: Predictive Modeling with Logistic Regression using SAS
- Offered by SAS. This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. This course also ... Enroll for free.


Courses

  • 0 reviews

    10 hours 3 minutes

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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.
  • 0 reviews

    11 hours 43 minutes

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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.
  • 0 reviews

    16 hours 34 minutes

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    This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. This course also discusses selecting variables and interactions, recoding categorical variables based on the smooth weight of evidence, assessing models, treating missing values, and using efficiency techniques for massive data sets. You learn to use logistic regression to model an individual's behavior as a function of known inputs, create effect plots and odds ratio plots, handle missing data values, and tackle multicollinearity in your predictors. You also learn to assess model performance and compare models.

Taught by

Jordan Bakerman and Michael J Patetta

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