Course info

Source-outline mode. Generate academy from uploaded outlines: XSAS01.pdf This course takes you from zero SAS experience to building complete analytics workflows inside SAS Studio. You will learn how to import, clean, visualize, test, and model data using core DATA and PROC steps, SAS Studio tasks, and key programming techniques. By the end, you will be able to produce reproducible SAS programs and stakeholder-ready reports. A single 18-hour, beginner-friendly course that takes a learner from no SAS experience to importing, cleaning, visualizing, testing, and modeling data entirely inside SAS Studio, following the uploaded XSAS01 outline exactly. What you will learn: - Use SAS Studio to write and run basic DATA and PROC steps, and to generate SAS code automatically from tasks. - Import, clean, and organize datasets using the INFILE technique, libraries, typecasting, missing value handling, and DROP/SET statements. - Engineer features and apply business rules using IF, IF-THEN-ELSE, SELECT-WHEN-OTHERWISE Statements, and DO Loops in DATA steps. - Filter and summarize data with PROC SQL Statements, SELECT-WHERE Statements, and WHERE Clauses, and cross-check results. - Create clear visualizations and maps, run core statistical procedures (T-Tests, ANOVA, correlations), and interpret them for non-technical audiences. - Fit appropriate regression models (Simple, Multiple, Logistic) in SAS Studio and explain coefficients or odds ratios in plain English. The following reference materials were provided as context. Use them as guidance only -- always prefer the latest, most current information over any potentially outdated content in these files. --- Reference: XSAS01.pdf --- ## SAS Fundamentals ## Overview 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. Prerequisites No prior knowledge of SAS is required. Number of Days 3 days ## 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.