Statistical Business Analyst
Aspirants who want to become Business Data Visualization analysts /experts and build a strong SAS programming foundation to manipulate data, perform queries and analyses, and generate reports. Additionally, wants to access the power of SAS for analysis and report generation on data using the point-and-click interface. This course helps you prepare you for the following certification exam(s): SAS Certified Base Programmer for SAS 9, SAS Certified Advanced Programmer for SAS 9 and SAS Certified Statistical Business Analyst Using SAS 9
Who should attend?
- Aspirants who want to become Business Data Visualization analysts /experts and build a strong SAS programming foundation to manipulate data, perform queries and analyses, and generate reports.
- Additionally, wants to access the power of SAS for analysis and report generation on data using the point-and-click interface.
SAS Programming 1: Essentials
SAS Programming 2: Data Manipulation Techniques
- Navigate the SAS windowing environment.
- Navigate the SAS Enterprise Guide programming environment.
- Read various types of data into SAS data sets.
- Create SAS variables and subset data.
- Combine SAS data sets.
- Create and enhance listing and summary reports.
- Validate SAS data sets.
SAS Macro Language 1: Essentials
- Control SAS data set input and output.
- Combine SAS data sets.
- Summarize, read, and write different types of data.
- Perform DO loop and SAS array processing.
- Transform character, numeric, and date variables.
SAS SQL 1: Essentials
- Perform text substitution in SAS code
- Automate and customize the production of SAS code
- Conditionally or iteratively construct SAS code
- Use macro variables and macro functions.
SAS Programming 3: Advanced Techniques and Efficiencies
- Query and subset data
- Summarize and present data
- Combine tables, including complex joins and merges
- Create and modify table views and indexes
- Replace multiple data and proc steps with one sql query.
Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression
- Benchmark computer resource usage
- Control memory, i/o, and cpu resources
- Create and use indexes
- Combine data horizontally
- Use hash and hiter data step component objects and arrays as lookup tables
- Compress sas data sets
- Sample your sas data sets
- Create and use sas data views
- Safely reduce the length of numeric variables
- Create user-defined functions and informats.
Predictive Modeling Using Logistic Regression
- Prerequisite Basic Concepts
- Introduction to Statistics
- t Tests and Analysis of Variance
- Linear Regression
- Linear Regression Diagnostics
- Categorical Data Analysis
- Predictive Modeling
- Fitting the Model
- Preparing the Input Variables
- Classifier Performance
The fees is inclusive of:
- Training & Digital Badge.
- Course material.
- 2 attempts of Global certification.
Download Course Curriculum
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