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Business Analytics using SAS

Business Analytics Using SAS training course focuses on linear regression, logistics regression, Analysis of Variance (ANOVA), and regression diagnostics.

What will i learn?
  • you will learn SAS macros, Machine Learning, PROC SQL, procedure, statistical analysis and decision trees.
  • You will Learn data mining, data analytics, modeling techniques, visualization of data, predictive analysis
  • Generate descriptive statistics & explore data with graphs. Perform analysis of variance & apply multiple comparison tec...
  • Perform linear regression and assess the assumptions. Use regression model selection techniques to aid in the choice of...
  • Explore data analysis and perform linear regression
  • Illustrate the use of One-Way ANOVA and Two-Way ANOVA
  • Conduct regression diagnostics and find out the influential observations. Identify the use of logistic regression and ta...
  • Interpretive predictive modeling and Adjustments for Oversampling. Demonstrate the use of nonlinearities and multilayer...

Business Analytics Using SAS training course 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.  

Business Analytics 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. This course (or equivalent knowledge) is a prerequisite to many of the courses in the statistical analysis curriculum. A more advanced treatment of ANOVA and regression occurs in the Statistics ANOVA and Regression course. A more advanced treatment of logistic regression occurs in the Categorical Data Analysis Using Logistic Regression course and the Predictive Modeling Using Logistic Regression course. 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.There are numerous hands-on practices integrated throughout the three courses of the program. Data examples are general enough to be applicable to a broad range of subject areas. Specific examples you will see in the courses address agriculture, manufacturing, health care, banking, retail, and nonprofit.

For more inquiries, visit our near BIT Training center or e-mail on inquiry@bitbaroda.com or visit one of the BIT Training Centers located in Vadodara (Manjalpur, Sayajigunj, Waghodiya).

  • Basic understanding of statistics covering p-values, hypothesis testing, analysis of variance, and regression
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