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SAS Certification Prep Guide

- Statistical Business Analysis Using SAS9

Über SAS Certification Prep Guide

Must-have study guide for the SAS® Certified Statistical Business Analyst Using SAS®9: Regression and Modeling exam! Written for both new and experienced SAS programmers, the SAS® Certification Prep Guide: Statistical Business Analysis Using SAS®9 is an in-depth prep guide for the SAS® Certified Statistical Business Analyst Using SAS®9: Regression and Modeling exam. The authors step through identifying the business question, generating results with SAS, and interpreting the output in a business context. The case study approach uses both real and simulated data to master the content of the certification exam. Each chapter also includes a quiz aimed at testing the reader's comprehension of the material presented. Major topics include: ANOVA Linear Regression Logistic Regression Inputs for Predictive Modeling Model Performance For those new to statistical topics or those needing a review of statistical foundations, this book also serves as an excellent reference guide for understanding descriptive and inferential statistics. Appendices can be found here.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9781642951806
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 414
  • Veröffentlicht:
  • 18. Dezember 2018
  • Abmessungen:
  • 279x216x24 mm.
  • Gewicht:
  • 1243 g.
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Beschreibung von SAS Certification Prep Guide

Must-have study guide for the SAS® Certified Statistical Business Analyst Using SAS®9: Regression and Modeling exam!

Written for both new and experienced SAS programmers, the SAS® Certification Prep Guide: Statistical Business Analysis Using SAS®9 is an in-depth prep guide for the SAS® Certified Statistical Business Analyst Using SAS®9: Regression and Modeling exam.

The authors step through identifying the business question, generating results with SAS, and interpreting the output in a business context. The case study approach uses both real and simulated data to master the content of the certification exam. Each chapter also includes a quiz aimed at testing the reader's comprehension of the material presented.

Major topics include:
ANOVA
Linear Regression
Logistic Regression
Inputs for Predictive Modeling
Model Performance

For those new to statistical topics or those needing a review of statistical foundations, this book also serves as an excellent reference guide for understanding descriptive and inferential statistics.

Appendices can be found here.

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