Upcoming Classes 2021/2022

WUSS Online Classes 2021/2022 – UPCOMING CLASSES

In lieu of an annual conference, WUSS is offering an extensive menu of online training classes throughout 2021 and early 2022. Our classes are taught by seasoned industry experts and are a tremendous value at just $125 per class. All classes are held from 10am to 2pm PT (1pm to 5pm ET).

Scholarships: Click here for information about scholarships that are available to help make these classes accessible to everyone!

But wait, there’s more! Every class attendee is automatically entered in a drawing for a complimentary registration for the in-person WUSS 2022 conference in Burlingame, California. You’ll receive one entry per class. The more classes you take, the greater your chance of winning!

Register Now

Registration is NOW OPEN for all classes! Please click on each class title for a detailed description of the course and information about the instructors.

Date Course Title (click for description) Instructor(s)
NOVEMBER 2021
Nov 5 SAS Essentials (or How I Learned to Stop Worrying and Love Code) Part 1 – ENCORE Tasha Chapman
Nov 15 SAS Essentials (or How I Learned to Stop Worrying and Love Code) Part 2 Tasha Chapman
Nov 17 SAS Macro Quoting: Learning the Skills of a Macro Developer Russ Lavery
Nov 19 CDISC ADaM – Implementation by Example Richann Watson
Nov 29 Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling (Getting Started) Isaiah Lankham and Matthew Slaughter
DECEMBER 2021
Dec 2 Designing Effective Surveys: Using Social Science to Answer Your Questions Tasha Chapman
Dec 6 Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling (Beyond the Basics) Isaiah Lankham and Matthew Slaughter
Dec 7 Fifty-Five Functions to Supercharge Your SAS® Code Josh Horstman
Dec 9 Hands-On Functions: How to Build Your Own User-Defined FCMP Functions and Macro Functions Troy Martin Hughes
JANUARY 2022
Jan 17 SAS + R Part 1: Connecting SAS and R in Your Data Science Workflow – ENCORE Hunter Glanz
Jan 19 SAS + R Part 2: Using R Shiny to Make Your Data Wrangling and Visualization Interactive – ENCORE Hunter Glanz
Jan 25 Custom Excel Reports Using PROC REPORT and the ODS Excel Destination Kirk Paul Lafler
Jan 27 SAS Essentials (or How I Learned to Stop Worrying and Love Code) Part 3 Tasha Chapman
FEBRUARY 2022
Feb 1 Take Advantage of Public Use Datasets (PUFs) to Learn SAS® Analytical, Graphical and Reporting Techniques, Analytic and Data Management Tools, and Explore Specialized Techniques Louise Hadden
Feb 8 Hands-On Data-Driven Design: Developing More Flexible, Reusable, Configurable SAS Software Troy Martin Hughes
Feb 11 Favorite FunKey Functions: Functions for Your Programming Toolbox Richann Watson
Feb 16 Basic Python Analytics: Do Common SAS Things in Python-Pandas Russ Lavery
Feb 18 Essentials of Statistical Graphics Procedures Sanjay Matange
Feb 25 Getting the Most Out of the Graph Template Language Dan Heath

Refund Policy: Refunds are only available upon request received up to 3 business days prior to the start of the class. Any refunds will deduct $25 per attendee per class for losses due to credit card processing and online registration charges. However, attendee substitutions are free at any time. Contact Western Users of SAS Software at registrar@wuss.org for substitution information or to request a refund. If classes are canceled due to low enrollment, the registrant will receive a full refund.

Course Descriptions







SAS Essentials (or How I Learned to Stop Worrying and Love Code) Part 1 – ENCORE

Tasha Chapman
Friday, November 5, 2021, 10:00am-2:00pm Pacific Time

SAS Essentials is a three-part instructor-led course that provides a thorough introduction to the basics of SAS programming including DATA steps, PROC steps, and the Output Delivery System. In these classes we focus entirely on coding, providing a fundamental education in how SAS thinks and unlocking the power to use the incredible versatility of SAS code. Whether you’re entirely new to SAS, new to coding, or just want to brush up on the fundamentals, these classes are for you.

Part 1: DATA steps and data manipulation (or How to Train Your SAS Datasets)

Together we’ll walk through the fundamental building blocks of a SAS program with a deep dive into DATA steps and data manipulation, including SAS libraries, conditional processing, functions, and more.





SAS Essentials (or How I Learned to Stop Worrying and Love Code) Part 2

Tasha Chapman
Monday, November 15, 2021, 10:00am-2:00pm Pacific Time

SAS Essentials is a three-part instructor-led course that provides a thorough introduction to the basics of SAS programming including DATA steps, PROC steps, and the Output Delivery System. In these classes we focus entirely on coding, providing a fundamental education in how SAS thinks and unlocking the power to use the incredible versatility of SAS code. Whether you’re entirely new to SAS, new to coding, or just want to brush up on the fundamentals, these classes are for you.

Part 2: PROC steps and basic reporting (or How to Succeed in SAS Without Really Trying)

This course will feature a showcase of the most common reporting procedures, including MEANS, FREQ, PRINT, TABULATE, and REPORT. We’ll also walk through the Output Delivery System and how it can be used to build professional reports the easy way.





SAS Macro Quoting: Learning the Skills of a Macro Developer

Russ Lavery
Wednesday, November 17, 2021, 10:00am-2:00pm Pacific Time

Attending this seminar that will give people the skills to move from being a macro writer to macro developer by understanding macro quoting. It works through more macro quoting examples than exist in all other online materials – combined.

This seminar focuses on using examples, and animated PowerPoints of the internal workings of the SAS system, to make words in the documentation clear and understandable. This seminar is effective for several reasons. Firstly, pictures/maps of the system are easier to understand than words when establishing relationships among system components. Secondly, a programmer must understand the sequence, and timing, of the steps in macro quoting in order to write/debug macros. This is best communicated as a series of “detailed moving images” that show the states of different parts of the system.

The moving graphical presentation has several advantages:

  • The picture of the process allows a reader to “check their understanding”. If the picture agrees with an attendee’s understanding of the words, the concept has been understood. If the attendee wants to ask questions, the map/picture allows the attendee to ask very specific/focused question and get answers that address their point of confusion.
  • This graphic presentation of the material helps bridge language barriers (I’ve done this in China 3 times). When English skills are lacking, the picture provides a second channel of communication.
  • The macro quoting process is complex and understanding/learning the process requires a student “hold the state of the system in their memory.” Using pictures of the system greatly reduces the mental complexity (human memory needs) of the learning process.





CDISC ADaM – Implementation by Example

Richann Watson
Friday, November 19, 2021, 10:00am-2:00pm Pacific Time

This course will provide a high-level overview of some of basic ADaM concepts. It is assumed that the attendee will have a fundamental knowledge of the different ADaM structures and principles. The primary focus of the course is to illustrate the implementation of some of the concepts found in both the ADaM Implementation Guide (ADaM IG) and the ADaM Structure for Occurrence Data (OCCDS) documents. Items covered include setting up subject level analysis data set (ADSL) for common trial designs and walking through the process of creating a basic data structure (BDS) starting from a simple BDS and building on it to structure a data set that will support one or more analyses. Additionally, the course will demonstrate how to implement some variables that are only found in OCCDS, such as the standardized MedDRA query (SMQ) and customized query (CQ) variables.





Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling (Getting Started)

Isaiah Lankham and Matthew Slaughter
Monday, November 29, 2021, 10:00am-2:00pm Pacific Time

Interested in learning Python? How about learning to make Python and SAS work together?

In this class, we’ll practice writing Python scripts using Google Colab (https://colab.research.google.com/), which is a free online implementation of JupyterLab, and we’ll link to SAS OnDemand for Academics (https://welcome.oda.sas.com/) to access the SAS analytical engine. We’ll also learn to use the popular pandas package, whose DataFrame objects are the Python equivalent of SAS datasets.

Along the way, we’ll work through common data-analysis tasks using both regular SAS code and Python together with the SASPy package, highlighting important tradeoffs for each and emphasizing the value of being a polyglot programmer fluent in multiple languages. This will include a beginner-friendly overview of Python syntax and data structures.

SASPy is a module developed by SAS Institute for the Python programming language, providing an alternative interface to the SAS system. With SASPy, SAS procedures can be executed in Python scripts using Python syntax, and data can be transferred between SAS datasets and their Python DataFrame equivalent. This allows SAS programmers to take advantage of the flexibility of Python for flow control, and Python programmers can incorporate SAS analytics into their scripts and applications.

This class is aimed at SAS programmers of all skill levels, including those with no prior experience using Python or JupyterLab. However, some examples will assume familiarity with the Output Delivery System, PROC SQL, and the SAS Macro Facility. Accounts for Google and SAS OnDemand for Academics will be needed to interact with code examples, and instructions for creating accounts will be distributed in advance. Also, all class materials will also be accessible (without any accounts needed) through https://github.com/saspy-bffs/wuss-2021-class





Designing Effective Surveys: Using Social Science to Answer Your Questions

Tasha Chapman
Thursday, December 2, 2021, 10:00am-2:00pm Pacific Time

When we want to know what’s going on in the minds of our customers, clients, and stakeholders we often develop a survey. However, gathering public opinion is not as simple as asking and answering. In fact, poorly designed questions actually frustrate participants and produce useless – or worse, inaccurate – results.

Don’t waste another minute creating a survey that doesn’t elicit useful information! Learn the right way to design a questionnaire from a scientific perspective. This course will use the fundamentals of social science research to prepare attendees to make their next survey a targeted and informative success.





Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling (Beyond the Basics)

Isaiah Lankham and Matthew Slaughter
Monday, December 6, 2021, 10:00am-2:00pm Pacific Time

Are you familiar with Python syntax? Want to go beyond the basics, and use Python and SAS together like a pro?

As in the “Getting Started” version of this course, we’ll practice writing Python scripts using Google Colab (https://colab.research.google.com/), which is a free online implementation of JupyterLab, and we’ll link to SAS OnDemand for Academics (https://welcome.oda.sas.com/) to access the SAS analytical engine. We’ll also practice using the popular pandas package, whose DataFrame objects are the Python equivalent of SAS datasets.

Along the way, we’ll work through more advanced data-analysis tasks using both regular SAS code and Python together with the SASPy package, highlighting important tradeoffs for each and emphasizing the value of being a polyglot programmer fluent in multiple languages. For example, we’ll explore advanced data-manipulation techniques, using SASPy as an interface for SAS/STAT, calling web APIs, and creating simple Python web applications incorporating SAS analytics.

SASPy is a module developed by SAS Institute for the Python programming language, providing an alternative interface to the SAS system. With SASPy, SAS procedures can be executed in Python scripts using Python syntax, and data can be transferred between SAS datasets and their Python DataFrame equivalent. This allows SAS programmers to take advantage of the flexibility of Python for flow control, and Python programmers can incorporate SAS analytics into their scripts and applications.

This class is aimed at intermediate to advanced SAS programmers, but assumes only basic familiarity with Python syntax and pandas DataFrames. However, no knowledge of JupyterLab is assumed, and it’s not necessary to have taken our “Getting Started” class beforehand. Accounts for Google and SAS OnDemand for Academics will be needed to interact with code examples, and instructions for creating accounts will be distributed in advance. Also, all class materials will also be accessible (without any accounts needed) through https://github.com/saspy-bffs/wuss-2021-class





Fifty-Five Functions to Supercharge Your SAS® Code

Josh Horstman
Tuesday, December 7, 2021, 10:00am-2:00pm Pacific Time

The SAS System includes an extensive collection of nearly five hundred DATA step functions that can provide great utility and convenience for the programmer. Many of these are relatively new and unknown. In this half-day course, we’ll look at some SAS functions that should be in every programmer’s toolbox. Each function will be presented with concrete examples so you’ll be able to take what you’ve learned and put it to use right away. We will cover functions from a broad range of categories such as string manipulation functions, functions for controlling program logic, functions for handling dates and times, mathematical functions, and much more. This course is suitable for beginning SAS programmers, but even seasoned veterans will probably find something new!





Hands-On Functions: How to Build Your Own User-Defined FCMP Functions and Macro Functions

Troy Martin Hughes
Thursday, December 9, 2021, 10:00am-2:00pm Pacific Time

“User-defined” functions represent those functions that are created by SAS users, as contrasted with “built-in” functions, which are part of the out-of-the-box Base SAS module and the SAS language. SAS provides two methods to build user-defined functions, including the SAS macro language and the SAS Function Compiler (aka PROC FCMP). This introductory course demonstrates how to build user-defined functions (and subroutines)—including both macro functions and FCMP functions. No prior experience with the SAS macro language or PROC FCMP syntax is required.

User-defined functions improve software reusability—that is, the ability of code modules to be reused in future software projects, and to be reused by multiple SAS practitioners within a team or organization. This code reuse enables a function to be developed once but used repeatedly, which reduces the workload of the SAS practitioners who are writing programs, by enabling us to rely on previously built (and fully tested) code modules. Thus, user-defined functions lead to not only more flexible and configurable software but also a more productive, efficient SAS team.

This HANDS-ON workshop enables students to run all programs in real-time using SAS Display Manager, SAS Enterprise Guide, or SAS OnDemand for Academics.

Macro function topics include:

  • Gentle introduction to the SAS macro language, including differentiation between SAS macros and SAS macro functions
  • Differentiation between positional and keyword parameters
  • Defining optional parameters and default parameter values
  • Passing macro lists and two-dimensional data structures to functions
  • Use of the PARMBUFF option in the %MACRO statement to facilitate multi-element arguments
  • Macro function argument validation, exception handling, and use of global macro variables as return values / return codes

FCMP function topics include:

  • Gentle introduction to PROC FCMP syntax and the construction of user-defined functions and subroutines (with the FUNCTION and SUBROUTINE statements, respectively)
  • Use of the VARARGS option in the FUNCTION statement to enable multi-element arguments to be passed to functions, and OUTARGS option to modify multiple arguments (within a subroutine)
  • Passing character and/or numeric data types to functions
  • Passing arrays to functions, and utilizing arrays within functions
  • Declaring, initializing, and referencing hash objects within functions
  • Calling functions and subroutines from the DATA step, and from %SYSFUNC and %SYSCALL, respectively
  • Calling functions from PROC FORMAT






SAS + R Part 1: Connecting SAS and R in Your Data Science Workflow – ENCORE

Hunter Glanz
Monday, January 17, 2022, 10:00am-2:00pm Pacific Time

As robust statistical software packages, SAS and R boast a great number of tools for addressing all of your data-related needs. While there exists large overlap in what they provide, today’s statistical and data science problems increasingly involve multiple software packages. After all, if you have access to all of these tools then why not explore how they can improve your workflow! In this class we will explore the complete workflow of cleaning a dataset, exploring it, visualizing it using a combination of SAS and R.






SAS + R Part 2: Using R Shiny to Make Your Data Wrangling and Visualization Interactive – ENCORE

Hunter Glanz
Wednesday, January 19, 2022, 10:00am-2:00pm Pacific Time

While both SAS and R include a rich suite of tools for working with your data, there often exists a collection of tasks and activities that get repeated with every new dataset. Traditionally such repetition could be addressed by building macros or functions. R Shiny enhances this process by making your data work interactive! Not only can this save you some code and work, but it provides a way for consumers of your work to do all of your cool data science-y things without needing to know how to program. In this class we will build our very own basic shiny applications using R.





Custom Excel Reports Using PROC REPORT and the ODS Excel Destination

Kirk Paul Lafler
Tuesday, January 25, 2022, 10:00am-2:00pm Pacific Time

SAS® users everywhere turn to the REPORT procedure to customize and satisfy their reporting needs as they create and deliver quality “custom” detail and summary reports, and specialized output for management, end users, and customers. This popular course explores an assortment of techniques to create custom spreadsheets, reports and specialized output using PROC REPORT and the powerful ODS Excel destination. Attendees learn how to create detail and summary spreadsheets, reports and output using PROC REPORT; acquire useful Output Delivery System (ODS) skills; combine PROC REPORT and the powerful ODS Excel destination to produce quick and formatted detail and summary Excel workbook results; customize output and results with SAS-supplied styles; compute subtotals and totals at the end of a report using a COMPUTE Block; calculate percentages; produce statistics for analysis variables; apply conditional logic to control summary output rows; add background images; build custom autofilter drill-down (interactive) reports and Excel workbooks; and add traffic lighting scenarios to Excel workbooks.





SAS Essentials (or How I Learned to Stop Worrying and Love Code) Part 3

Tasha Chapman
Thursday, January 27, 2022, 10:00am-2:00pm Pacific Time

SAS Essentials is an instructor-led course that provides a thorough introduction to the basics of SAS programming including DATA steps, PROC steps, and the Output Delivery System. In this class we focus entirely on coding, providing a fundamental education in how SAS thinks and unlocking the power to use the incredible versatility of SAS code. Whether you’re entirely new to SAS, new to coding, or just want to brush up on the fundamentals, this class is for you.

Part 3: Introduction to intermediate topics (or How Green Was My SAS Code)

With the fundamentals under our belt, this course will show you tips and techniques for improving your SAS code exponentially with a brief introduction to tools like SQL, Arrays, Macros, and much more.





Take Advantage of Public Use Datasets (PUFs) to Learn SAS® Analytical, Graphical and Reporting Techniques, Analytic and Data Management Tools, and Explore Specialized Techniques

Louise Hadden
Tuesday, February 1, 2022, 10:00am-2:00pm Pacific Time

Interest in data sources useful for demonstrating statistical, graphical and reporting techniques has increased with the exponential growth of interest and activity in the fields of Data Science, Machine Learning, and Natural Language Processing. Thus, freely available and reliable banks of data have become highly sought after. This tutorial will introduce three high quality and robust data sources for analytic work suitable for journal submissions, and explore in depth public use data sets and BASE SAS tools that can be used to analyze and graphically represent measures and trends. These data sets include USAID’s Demographic and Health Surveys which include health survey data from Afghanistan to Zimbabwe; the Centers for Medicare and Medicaid Services’ Care Compare Tool (data.medicare.gov and data.cms.gov) focusing on nursing homes; and CDC’s National Health and Nutrition Examination Survey (NHANES) which will demonstrate how to work with a complex sampling design. Exploration of the NHANES survey will also include the use of National Cancer Institute (NCI) macros to analyze usual daily intake. The tutorial will prepare attendees to construct an analysis plan (AP) and standard operating procedures (SOPs) for researching, analyzing and documenting PUFs. SAS tools used will be standard statistical and reporting tools available in BASE SAS, as well as geographic tools including PROC GEOCODE.





Hands-On Data-Driven Design: Developing More Flexible, Reusable, Configurable SAS Software

Troy Martin Hughes
Tuesday, February 8, 2022, 10:00am-2:00pm Pacific Time

Attend and receive a FREE copy of the author’s 600-page book, SAS® Data-Driven Development: From Abstract Design to Dynamic Functionality, Second Edition, released in 2021. Students will receive the physical book in advance of this virtual training, which includes all course scenarios and code. Sample code will also be provided electronically so students can run all programs in real-time using SAS Display Manager, SAS Enterprise Guide, or SAS OnDemand for Academics.

This HANDS-ON workshop installs the student as the new SAS consultant within Scranton, Pennsylvania’s most infamous paper supply company — charged with improving software functionality and performance through data-driven software design. Navigate office intrigue and antics to gather software requirements, analyze hardcoded legacy SAS programs, and refactor (improve) software through data-driven design principles and methods. Help Jim, Dwight, Phyllis, and Stanley sell more paper through higher quality data-driven software!

Data-driven design describes software in which configuration items, business rules, data validation rules, data models, data dictionaries, report style, and other dynamic elements are maintained in external data structures — NOT in underlying code. Benefits include increased software flexibility, reusability, maintainability, modularity, readability, interoperability, extensibility, and configurability. In other words, data-driven design improves your software quality.

Topics include:

  • Compare undesirable hardcoded design with preferred data-driven design, and demonstrate the methods to help SAS practitioners refactor from the former to the latter
  • Build reusable procedures, functions, and call routines (subroutines) using SAS macros and PROC FCMP (the SAS function compiler)
  • Demonstrate built-in and user-defined data structures (including parameters, macro lists, arrays, hash objects, control tables, configuration files, data sets, Excel spreadsheets, CSV files, and CSS files)
  • Use SAS components that support data-driven development (including CALL EXECUTE, CNTLIN option in PROC FORMAT, SYSPARM option, SAS dictionary tables, and CSSSTYLE option in PROC REPORT)
  • Ingest positional flat files, CSV files, SAS data sets, and other transactional files, and dynamically identify altered or invalid file format/structure through prescriptive data dictionaries
  • Create color-coded, “traffic light” quality control reports that automatically identify bad data while standardizing good data
  • Configure the style (e.g., format, font, color scheme, graphics) of data products using user-defined SAS formats and CSS files
  • Learn how user-defined configuration files can facilitate software flexibility, by enabling different users to achieve dynamic functionality based on user-specified preferences that can be saved, modified, and shared with other users
  • Understand how master data management (MDM) can support data structures that are leveraged by SAS, Python, and other languages/applications simultaneously





Favorite FunKey Functions: Functions for Your Programming Toolbox

Richann Watson
Friday, February 11, 2022, 10:00am-2:00pm Pacific Time

Functions are an invaluable part of the programmer’s toolbox. While some functions are extremely popular, for good reason, there are some that could be considered hidden gems. This training will highlight less commonly used functions, such as the PRXCHANGE and PRXPARSE functions, which are essential for efficient string manipulation. Another example is the COALESCE(C) function, which can facilitate the population of missing values based on parameters, and more. This course will illustrate through examples these and more FunKey functions. Additionally, this course will explore the utility of writing functions with the FCMP procedure, which combines the reusability of macro processing with the power of functions, and learn to enhance SAS reporting with user-written style functions. The course is designed for everybody of all skill levels.





Basic Python Analytics: Do Common SAS Things in Python-Pandas

Russ Lavery
Wednesday, February 16, 2022, 10:00am-2:00pm Pacific Time

This seminar is intended to teach people how to do, in Python/Pandas, the things they routinely do in SAS.

This seminar will focus on: reading data into a data frame (a Python/Pandas name for a data set) , appending data frames, merging data frames, sub-setting data frames (e.g., find names & emails of all the customers from CA), plotting and different techniques for grouping/reporting (similar to a Proc SQL or a Proc Freq ). It will, lightly, cover the meaning of an object, class and a namespace.

Python is an object oriented language, with over 80 commonly used objects, and is conceptually very different from SAS. Python was not really designed – it grew from users adding new features. Python is very condensed and one python statement can execute several steps (and hidden loops). Unlike most of the talks on Youtube (where the presenter just reads the code he has typed) this will focus on the the internal steps and loops that the one line of code causes to execute. Understanding the internals is needed for debugging mistakes.

Python is a very big program and this seminar is going to focus on one part of Python – Pandas. Pandas is the Python module that access a table of data (think SAS dataset or Excel sheet). It will not cover Python as a web page tool. A lot of work can be done in Pandas – if the data is relatively clean and if the programmer makes few mistakes. If a programmer starts making mistakes, or the data is dirty, an understanding of Python itself is needed and is beyond the scope of this introductory seminar.





Essentials of Statistical Graphics Procedures

Sanjay Matange
Friday, February 18, 2022, 10:00am-2:00pm Pacific Time

The SAS Statistical Graphics (SG) Procedures help you create modern statistical graphs that are frequently used across many domains for visualization of data. In this half-day course, we will cover the key features of the SGPLOT, SGPANEL and SGSCATTER procedures. We will also build specific examples from the Health and Life Sciences domains such as the Forest Plot, Adverse Event Timelines, Survival Plot, Panel of LFT Shift from Baseline and more.

Course outline:

  • Brief overview of ODS Graphics.
  • Single cell graphs using the SGPLOT procedure.
  • Classification panels using the SGPANEL procedure.
  • Scatter plot panels using the SGSCATTER procedure.
  • Review of key SAS 9.4 features.

Prerequisites: This course is suitable for users with all levels of SAS programming knowledge.





Getting the Most Out of the Graph Template Language

Dan Heath
Friday, February 25, 2022, 10:00am-2:00pm Pacific Time

In this course, we will cover the fundamental concepts of the Graph Template Language (GTL), as well as advanced techniques that can be useful for certain types of displays. We will also spend some time discussing the ODS Graphics system and best practices on when to favor the use of GTL versus the SG procedures.

Meet the Instructors

Tasha Chapman has been using SAS since 2003 and an active member of the SAS User Community since 2006. Throughout her career she has championed continuing education and professional development, presented trainings and workshops at professional conferences across the country, sat as an executive committee member on nationally recognized associations, and founded two organizations dedicated to educating colleagues about research, data, and statistics. She was the chair of the Western Users of SAS Software Conference and Educational Forum in 2017.

Tasha received a Master’s Degree in Psychology, with an emphasis on personality assessment and psychometrics from the University of California, Riverside. Since 2005 she has worked for the State of Oregon as a lead research analyst providing data and policy analysis for Oregon OSHA, the Oregon Child Welfare Program, and the Oregon Health Authority. She lives in Salem, Oregon with her two adorable kids, Nadia and Atlas.

Hunter Glanz is an Associate Professor of Statistics and Data Science at California Polytechnic State University (Cal Poly, San Luis Obispo). He received a BS in Mathematics and a BS in Statistics from Cal Poly, San Luis Obispo followed by an MA and PhD in Statistics from Boston University. He maintains a passion for machine learning and statistical computing, and enjoys advancing education efforts in these areas. In particular, Cal Poly’s courses in R, SAS, and Python give him the opportunity to connect students with exciting data science topics amidst a firm grounding in communication of statistical ideas. Hunter serves on numerous committees and organizations dedicated to delivering cutting edge statistical and data science content to students and professionals alike. In particular, the ASA’s DataFest event at UCLA has been an extremely rewarding experience for the teams of Cal Poly students Hunter has had the pleasure of advising.
Louise Hadden has been using, and loving, SAS since the days of punch cards and computers the size of a not-so-tiny house. She spends most of her time in support of health policy analytics at Abt Associates Inc., and loves a good SAS reporting challenge. She is also the girl with the SAS tattoo!
Dan Heath is a principal systems developer at SAS Institute. A SAS user for more than 27 years, Dan specializes in SAS/GRAPH software, ODS Graphics, and related graphing technologies. Dan has been a speaker at a number of regional and local users’ group meetings, including SAS Global Forum, PharmaSUG, and WUSS. He received a BS degree in computer science from North Carolina State University.
Josh Horstman is an independent statistical programmer based in Indianapolis with 20 years’ experience using SAS in the life sciences industry. He specializes in analyzing clinical trial data, and his clients have included major pharmaceutical corporations, biotech companies, and research organizations. A SAS Certified Advanced Programmer, Josh loves coding and is a frequent presenter at SAS Global Forum and various regional and local SAS users’ group. Josh holds a bachelor’s degree in mathematics and computer science, and a master’s degree in statistics from Colorado State University.
Troy Martin Hughes has been a SAS practitioner for more than 20 years, has managed SAS projects in support of federal, state, and local government initiatives, and is a SAS Certified Advanced Programmer, SAS Certified Base Programmer, SAS Certified Clinical Trials Programmer, and SAS Professional V8. He has given more than 100 presentations, trainings, and hands-on workshops at SAS conferences, including at SAS Global Forum, SAS Analytics Experience, WUSS, SCSUG, SESUG, MWSUG, PharmaSUG, BASAS, and BASUG. He has authored two groundbreaking books that model software design and development best practices:

  • SAS® Data-Driven Development: From Abstract Design to Dynamic Functionality, Second Edition (2021)
  • SAS® Data Analytic Development: Dimensions of Software Quality (2016)

Troy has an MBA in information systems management as well as other credentials, including: PMP, PMI-RMP, PMI-PBA, PMI-ACP, SSCP, CISSP, CSSLP, Network+, Security+, CySA+, CASP+, CISA, CGEIT, CISM, CRISC, ITIL Foundation, CSM, CSD, A-CSD, CSPO, CSP, CSP-SM, CSP-PO, and SAFe Government Practitioner (SGF). He is a US Navy veteran with two tours of duty in Afghanistan.

Kirk Paul Lafler is an entrepreneur, consultant, programmer and educator, and has been a SAS user since 1979. Kirk is a lecturer and adjunct professor at San Diego State University; an advisor and adjunct professor at the University of California San Diego Extension; and teaches dozens of SAS, SQL, Excel, R and Python courses, seminars, workshops, and webinars to users around the world. As the author of several books including PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press. 2019) along with hundreds of papers and articles on a variety of SAS topics; Kirk has been selected as an Invited speaker, educator, keynote and section leader at SAS conferences and meetings worldwide; and is the recipient of 25 “Best” contributed paper, hands-on workshop (HOW), and poster awards.
Isaiah Lankham is a polyglot data analyst for the University of California’s systemwide office in Oakland, CA, specializing in data analysis and visualization using Tableau, SAS, and Python. Initially trained as a mathematician and educator, Isaiah is also an adjunct faculty member for the Statistics Department at California State University, East Bay, regularly teaching graduate SAS programming courses.
Russ Lavery is a frequent and multiple-award winning presenter at SAS and other programming conferences. He has been the technical reviewer for five books by SAS press and has lectured all over the U.S. in Europe and in Asia.
Sanjay Matange is an expert in the field of data visualization using SAS graphics software including the SG procedures and GTL. Sanjay worked at SAS for 29 years where he was responsible for the development of ODS Graphics. Sanjay is co-author of four patents and the author of four SAS Press books. Sanjay was also the main author of Graphically Speaking SAS blog for 8 years.
Matthew Slaughter, MSBA is an Advanced SAS Certified Programmer and a Statistical Research Analyst at the Kaiser Permanente Center for Health Research in Portland, Oregon. Specializing in clinical prediction modeling, Matthew provides data management, programming, and analytical support to research projects in various topic areas.
Richann Watson is an independent statistical programmer and CDISC consultant based in Ohio. She has been using SAS since 1996 with most of her experience being in the life sciences industry. She specializes in analyzing clinical trial data and implementing CDISC standards. Additionally, she is a member of the CDISC ADaM team and various sub-teams.

Richann loves to code and is an active participant and leader in the SAS User Group community. She has presented numerous papers, posters, and training seminars at SAS Global Forum, PharmaSUG, and various regional and local SAS user group meetings. Richann holds a bachelor’s degree in mathematics and computer science from Northern Kentucky University and master’s degree in statistics from Miami University.