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SAS Fundamentals

  • All levels
  • 18 and older
  • $1,195
  • 10940 Wilshire Blvd, Santa Monica, CA
  • 20 hours & 15 minutes over 3 sessions

Start Dates (0)

  • $1,195
  • ONLC Training Center - LA (West) @ 10940 Wilshire Blvd Ste 600, Santa Monica, CA 90024
  • 20 hours & 15 minutes over 3 sessions
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Class Description

Description

What you'll learn in this data analyst training:

Do you want to create data analysis reports without writing a line of code? This course introduces SAS programming using SAS Studio. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. All that you will learn in this course, you can apply seamlessly using SAS Enterprise Guide or SAS Viya as all platforms use the same programming language and same syntax.

It is easier to learn SAS than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks. If you use any other SAS product, this course will cover the SAS programming syntax and fundamentals needed to do your data reports.

The course provides real-life examples including analyzing election predictions, stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS.

You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS graphical user interface. The course includes explanations of the code that SAS IDE generates automatically. You will learn how to edit this code to perform more complicated advanced tasks.

You will:

  • Become familiar with SAS IDE
  • Understand essential visualizations
  • Know the fundamental statistical analysis required in most data science and analytics reports
  • Clean the most common data set problems
  • Use linear progression for data prediction
  • Write programs in SAS

Intended Audience

This class is most appropriate for data scientists and those wanting data analytics. Individuals mastering the content of this class will be qualified to pass the SAS certification exams for SAS 9.4 Base Programming (A00-231) and SAS 9.4 Programming Fundamentals (A00-215). Also, class participants will be on their way toward being qualified for the SAS 9.4 Advanced Programming (A00-212). Speak with the instructor or to a customer service representative to get additional supplemental material to prepare for the Advanced Programming certification.

Course Outline

Part I: Basics:

  • Data Science in Action
  • Data Science Process

Case Study: Presidential Elections in Maine:

  • Population
  • Gender
  • Race
  • Age
  • Voter Turnout
  • Winning Candidates in 2012
  • Categories/Issues
  • Factors Affecting Maine’s Economy
  • Modeling
  • My 2016 Predictions
  • My 2020 Predictions

Getting Started:

  • How Do You Install SAS Studio?
  • What Is SAS and SAS Studio?
  • Tour
  • Tasks
  • Reports
  • Graphs
  • Snippets
  • Main Components of a SAS Program
  • Data Step
  • Variable Types
  • Proc Step
  • Libraries
  • Accessing Your Existing Local Files
  • Accessing Data in SAS Libraries
  • Create a New Library
  • Add a New Table to the Library
  • INFILE technique

Data Visualization:

  • Scatter Plot
  • Scatter Plot Code
  • Scatter Plot Relationships
  • Plotting More Than One Scatter Plot in the Same Image
  • Histogram
  • Appearance Tab
  • Series Plot
  • Bar Chart
  • How Do You Sort A Bar Chart?
  • Create a Histogram Using a Bar Chart
  • Bubble Chart
  • Maps
  • Bubble Map
  • Cluster Analysis

Statistical Analysis and Linear Models:

  • Statistical Analysis
  • One-Way Frequency
  • Summary Statistics
  • Correlation Analysis
  • T-Tests
  • One-Sample T-tests
  • Paired-sample T-test
  • Two-Sample T-tests
  • Linear Models
  • One-Way ANOVA
  • N-Way ANOVA

Advanced Data Preprocessing and Feature Engineering:

  • Comment Statement
  • Arithmetic Operators
  • How to Represent Missing Values in Raw Data
  • Comparison Operators
  • PROC SQL Statement
  • SELECT-WHERE Statement
  • WHERE Clause
  • SELECT-WHEN-OTHERWISE Statement
  • DO Loops

Preparing Data for Analysis:

  • Label
  • Format
  • Create New Variables
  • Rearrange the Dataset Variables
  • IF Statement IF (Condition) Without THEN statement
  • IF-THEN Statement
  • IF-THEN-ELSE Statement
  • DROP Statement
  • SET Statement

Regression:

  • Simple Linear Regression
  • Multiple Linear Regression
  • Logistic Regression
Project/Case Study

We will work on another data set to practice by hand everything we learned throughout the course. We will clean the data column by column including character, numeric, date and time variables and how to do typecasting. We will find the correlation between the outcome and the variables.

Refund Policy

Cancellation / Reschedule by Student

Because we must schedule rooms, ship course materials, assign instructors and provision computer resources well in advance, it is important students alert us ASAP with any cancel/reschedule requests.

Please note the following policies:

  • If requested 16 or more calendar days before the class
    • Cancellation requests made in this timeframe are eligible for refund less 5% cancellation fee.
    • Reschedule requests made in this timeframe will be accommodated if availability exists and will be processed at no additional charge.
  • If requested 15 calendar days or less before the class
    • Cancellation or Reschedule requests made by the student 15 calendar days or less before the class starts will be charged 100% the course fee and are not entitled to a refund.

Substitutions

  • If you are unable to attend your class, a substitute who meets the course prerequisites may attend in your place at no additional charge for the original class title, date and location. If you cannot find a substitute, you will be subject to the class cancellation policy.

Make-up Policy

Students are permitted one (1) Make-Up opportunity to attend an instructor-led class that was paid for but not previously attended for no additional charge.

  • Make-Up class registrations are subject to availability and are not entitled to refund.
  • Students may not reschedule a Make-up class registration.
  • Any no shows or cancellations forfeit their one Make-up opportunity.

Additionally, ONLC reserves the right to retire courses due to lack of demand. Retired classes are not available for Make-Up.

In the event that an instructor or the school needs to cancel at the last minute, students will receive a refund less a 5% non-refundable registration fee.

In any event where a customer wants to cancel their enrollment and is eligible for a full refund, a 5% processing fee will be deducted from the refund amount.

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ONLC Training Centers

ONLC Training Centers was founded in 1983 when Jim Palic and Andy Williamson left their positions as mainframe programmers with the Dupont Company to start one of the industry's first computer training companies.

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