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 Coursera - SAS Statistical Business Analyst Professional Certificate by SAS

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Coursera - SAS Statistical Business  Analyst Professional Certificate by SAS Empty
MensajeTema: Coursera - SAS Statistical Business Analyst Professional Certificate by SAS   Coursera - SAS Statistical Business  Analyst Professional Certificate by SAS EmptyMiér Nov 04, 2020 5:34 am

Coursera - SAS Statistical Business  Analyst Professional Certificate by SAS 15f91ff4aa0b89ab437355fa71eb654c

Coursera - SAS Statistical Business Analyst Professional Certificate by SAS
Video: .mp4 (1280x720) | Audio: AAC, 44100 kHz, 2ch | Size: 1.08 Gb | Materials: PDF
Genre: eLearning Video | Duration: 11h 28m | Language: English
Distinguish Yourself as a Modeler. You will acquire SAS statistics, modeling, and programming skills including ANOVA, regression, logistic regression, business applications of modeling, and challenges of modeling.

Introduction to Statistical Analysis: Hypothesis Testing
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
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.

Predictive Modeling with Logistic Regression using SAS
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 Descriptions and odds ratio Descriptions, handle missing data values, and tackle multicollinearity in your predictors. You also learn to assess model performance and compare models.

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