Conference Workshops

Conference Workshops offer the bonus of additional educational experiences for SESUG Conference attendees.  We have talented, recognized, and experienced instructors prepared to share their knowledge in these 4-hour sessions.

SESUG is scheduling six concurrent workshops this year on Sunday, October 20 from 8 am – noon and 1 pm – 5 pm.

The workshops cover a wide variety of topics and skill levels.  These 4-hour workshops will appeal to everyone interested in exceptional in-depth training.  Please note that workshops are an extra fee event at SESUG.

Peering into the Future: Introduction to Time Series Methods for Forecasting David A. Dickey 8am-12pm
Understanding Why Your Macros Don't Work Michelle Buchecker 8am-12pm
Methods of Sharing Data between SAS® and Excel® Using Basic SAS Techniques William E. Benjamin, Jr. 8am-12pm
Demystifying SQL Christianna Williams 1-5pm
SG Procedures and ODS GRAPHICS for the Non-Statistician Cynthia Zender 1-5pm
Handy SAS® Functions Taylor Lewis 1-5pm

Early Online Registration Fee $125
Regular Onsite Registration $150
Administrative Fee for Workshop Only $25 (no conference registration)


For information on registering for a workshop or the conference, please see Registration Information.

   SESUG 2013 Weekend Workshops

Peering into the Future: Introduction to Time Series Methods for Forecasting

Scheduled Time:  Sunday 8:00 am – 12:00 pm

Intended Audience:  Introductory course.  Knowledge of basic statistical methods, especially regression, required.

Instructor:  David A. Dickey, North Carolina State University

This workshop will provide a practical guide to time series analysis and forecasting, focusing on examples and applications in SAS.  Students will learn how to recognize autocorrelation when they see it and how to incorporate autocorrelation into their modeling.  They will see the dangers of ignoring autocorrelation.  Models in the ARIMA class and their identification, fitting, and diagnostic testing will be emphasized and extended to models with deterministic trend functions (inputs) and ARMA errors.  Diagnosing stationarity, a critical feature for proper analysis, will be demonstrated.  After the course the student should be able to identify, fit, and forecast with this class of time series models and should be aware of the consequences of having autocorrelated data.  They should be able to recognize nonstationary cases in which the differences in the data, rather than the levels, should be analyzed.  Underlying ideas and interpretation of output, rather than code, will be emphasized and no previous experience with SAS/ETS products is needed, however a familiarity with basic statistical inference and regression will be assumed.  The SAS procedures PROC ARIMA and PROC AUTOREG will be demonstrated.

Instructor Bio:   David A. Dickey received his PhD in statistics in 1976 from Iowa State University working with Dr. Wayne A. Fuller.  Dickey is William Neal Reynolds professor of statistics at North Carolina State University.  He is co-author of several books on statistics, including “The SAS System for Forecasting Time Series,” a publication of SAS Institute.  He has presented at many conferences including SESUG, SUGI, and SAS Global Forum.  He has been a contact instructor for SAS Institute since 1981 teaching courses in statistical methodology, including time series, and has helped write some of their course notes.  Recently Dickey has been teaching for the NC State University Institute for Advanced Analytics that offers an intensive applied Master’s degree in a 9-month cohort program.

Understanding Why Your Macros Don't Work

Scheduled Time:  Sunday 8:00 am – 12:00 pm

Intended Audience:  For those who want to know more about the “whys” of the SAS Macro language so that they can spend less time using trial and error with your macro code.

Instructor:  Michelle Buchecker, SAS

This brain-teasing seminar will discuss the behind the scenes workings of the macro facility and explain why macro variables you thought would resolve don't, why you need an extra period or four after a macro variable reference, why you care about the difference between %LET and CALL SYMPUT, and what all those extra ampersands are for.  The objectives of this workshop are:

  • When and where you should put quotes
  • Describe why you sometimes need extra periods
  • Identify why extra ampersands are needed
  • Determine the difference between %LET and CALL SYMPUT
  • Figuring how and why a macro variable can't be found even though you know you created it
  • When to use Quoting Functions
Some macro knowledge is recommended before attending this seminar.

Instructor Bio:   Michelle Buchecker is an Education Director for SAS.  She has been an instructor at SAS for over 20 years.  Her specialties include BASE SAS, Macro, SAS/Connect (including parallel and distributed processing), OLAP and BI, and some Solutions such as Customer Intelligence.  Prior to joining SAS, Michelle was a SAS programmer at IBM reading SMF mainframe data.

Methods of Sharing Data between SAS® and Excel® Using Basic SAS Techniques

Scheduled Time:  Sunday 8:00 am – 12:00 pm

Intended Audience:  Introductory survey course

Instructor:  William E. Benjamin Jr., Owl Computer Consultancy, LLC.

This course will examine methods intermediate level SAS programmers may be familiar with.  The detailed examples presented in the course demonstrate movement of data between SAS and Excel file structures.  These concepts and techniques will include the following:

  1. Cut and paste, and accessing Excel data from the SAS Display Manager Window and toolbar
  2. Conversion of text files to an Excel format using built in Excel data conversion features
  3. PROC EXPORT and PROC IMPORT features and examples
  4. SAS LIBNAME methods and examples
  5. SAS Enterprise Guide methods to access Excel files
  6. ODS Tagset Template output files (CSV, HTLM, MSOFFICE2K, and EXCELXP)
  7. SAS procedures that output Tagset Template files
Several of these features are available with only BASE SAS installed, however others will require the installation of SAS/ACCESS for PC File Format software or SAS Enterprise Guide software.  Each of the examples will be shown and explained in enough detail to allow application by the user when the course is complete.  While most of these techniques are common and widely used, they are also feature rich and permit access to Excel files in ways that are not frequently used.  The class will show you how to differentiate features that access 32-bit and 64-bit Excel files and how to change the format of variables read from an Excel file using DATASET options to read specific Excel columns.

This class will touch upon many topics and techniques.  The intent of the class is to provide the student with the resources and knowledge that will make them aware of the varied options available for transferring data between SAS and Excel.  Many of the options provided by the SAS tools and Procedures vary slightly in their definitions but produce very different results.

Instructor Bio:   William E. Benjamin, Jr. is a consultant and founder of OWL Computer Consultancy, LLC in Phoenix AZ, his expertise includes Base SAS Software, SAS Macros, SQL, and Transferring data between SAS and Excel.  William provides consulting and training services to SAS users.  He has been a SAS software user since 1983 and a computer programmer since 1973.  William has written and presented papers at local, regional, and national SAS conferences.  In 1999 William authored one of 22 SAS Observation’s Online articles for SAS Institute.  His programming experience spans from vacuum tube mainframes, to current PC computers.  Look for his new SAS Press book later this year about Transferring data between SAS and Excel.

Demystifying SQL

Scheduled Time:  Sunday 1:00 pm – 5:00 pm

Intended Audience:  Beginner with a basic understanding of the structure of a SAS data set.

Instructor:  Christianna Williams, Independent Consultant

Subqueries, inline views, outer joins, Cartesian products, HAVING expressions, Set operators, INTO clauses…  Just the terminology of SQL can be rather daunting for SAS programmers raised on getting the DATA step to do our bidding for data manipulation. Not to mention the profusion of commas and complete dearth of semi-colons found in a PROC SQL step!  Nonetheless, even the most die-hard DATA Step programmers must grudgingly acknowledge that there are some tasks – such as the many-to-many merge or the “not-quite-equi-join” – that would require Herculean effort to accomplish with DATA steps but can be achieved amazingly concisely, even elegantly, using PROC SQL.  This updated workshop will present a series of increasingly complex examples to illustrate the function of each of PROC SQL’s clauses, with particular focus on summarization/aggregation and a variety of joins.  Additionally, the examples will illuminate how SQL “thinks” about rows and columns, some of which can cause unexpected results for the unwary user.  And after all, PROC SQL is part of Base SAS; so, though you may need to learn a few new keywords to become an SQL wizard, no special license is required!

Instructor Bio:   Christianna Williams, PhD is an independent consultant based in Chapel Hill, North Carolina, focusing on study design and statistical analyses and reporting in epidemiology and health services research.  Arguably, she spent way too much time in school and holds degrees from Duke University, Yale University and the University of California at Berkeley.  Christianna started using SAS as a graduate student in population biology in 1985 and is still learning!  She is a frequent presenter at local and regional user group conferences as well as SAS Global Forum, and has been teaching about PROC SQL for more than 10 years.  She also devotes as much time as possible to her other passions: running, vegetarian cooking and reading novels.

SG Procedures and ODS GRAPHICS for the Non-Statistician

Scheduled Time:  Sunday 1:00 pm – 5:00 pm

Intended Audience:  All levels

Instructor:  Cynthia Zender, SAS

Do you need to produce simple series plots and bar charts and maybe the occasional box plot?  Do you want to generate "small multiple" or paneled charts, as recommended by Edward Tufte?  This seminar illustrates how to use the new SG procedures, in particular, SGPLOT and SGPANEL to produce simple plots and bar charts.  Primary SGPLOT types covered will be VBAR, HBAR, SERIES, VBOX and HBOX.  Once you know the basics of the SGPLOT statements to produce single graphs, learning SGPANEL to created paneled output will be a cinch.  Through concrete examples, this seminar will guide you through the basics of producing and customizing simple graphs using the new SG procedures.  (Note: The SGSCATTER and SGRENDER procedures are topics that are not covered in this seminar.)  In addition, use of the ODS GRAPHICS statement for setting or changing graph options will be covered.

Instructor Bio:   Cynthia Zender has been with SAS since 1996 as an instructor and course developer.  She currently serves as the Curriculum Manager for the Report Writing and Output Delivery System curriculum.  Cynthia is a SAS Certified Professional, with over 25 years of experience programming and reporting with SAS.  Prior to joining SAS, she worked with a variety of industries (including education, public utilities, and telecom), using SAS for application development and report writing.

Handy SAS® Functions

Scheduled Time:  Sunday 1:00 pm – 5:00 pm

Intended Audience:  Any and all SAS programmers

Instructor:  Taylor Lewis, University of Maryland

This course highlights a number of extremely useful SAS functions that deserve a place in every SAS programmer’s repertoire.  Driven by a broad range of examples, the course consists of four modules:

  1. Manipulating and Extracting Information from Character Variables
  2. Transforming and Calculating Descriptive Statistics about Numeric Variables
  3. Functions that Return Information about Attributes of a Data Set
  4. Date and Time Functions
The target audience is any SAS programmer who wants to learn how to better harness the power of these built-in tools to simplify the amount of syntax required for performing a variety of everyday coding tasks.  Since many of these functions are relatively new, even intermediate or advanced programmers will find the course useful.

Instructor Bio:   Taylor Lewis is a mathematical statistician for the U.S. Office of Personnel Management and a PhD student at the Joint Program in Survey Methodology at the University of Maryland, College Park.  An avid SAS user for over 10 years, he holds the SAS Certified Advanced programmer credential and has presented numerous papers and workshops at SAS conferences covering a variety of topics.

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