You can extend your educational opportunities in a number of ways at SAS Global Forum 2012. Sign up to participate in a Pre-Conference Seminar or Statistical Tutorial on Sunday, or arrive earlier for SAS Training Courses.
Pre-Conference Seminars & Statistical Tutorials
Sunday, April 22
Seminars and Statistical Tutorials are extra-fee events costing $155 each and include relevant handouts. The Statistical Tutorials are taught by SAS R&D staff.
|8:00 am - 11:30 am
|12:30 pm - 4:00 pm
|Best Practices in Base SAS Coding||Building Powerful Reusable Tools with the SAS Macro Language|
|Excel VBA: When You Have to Step Outside SAS||Creating Complex Reports|
|Innovative Tips and Techniques: Doing More in the DATA Step||SAS SQL: Building on the Basics|
|SAS Administration: Understanding Architecture and Administration||SG (Statistical Graphics) Procedures and ODS GRAPHICS for the Nonstatistician|
|8:00 am - 10:00 am
|10:30 am - 12:30 pm
|Creating Statistical Graphics with ODS in SAS||Data Simulation for Evaluating Statistical Methods in SAS|
|SAS Procedures for Analyzing Survey Data||Introduction to Bayesian Analysis Using SAS Software|
These extra-fee items are only available as additions to a conference registration. Package 3 includes your choice of one Sunday Pre-Conference Seminar or Statistical Tutorial. EPTO units may not be used to pay for these items.
8:00 - 11:30 a.m.
Best Practices in Base SAS® Coding
Instructor: Brian Gayle, SAS
How you write your SAS code can have a tremendous impact on the use of computer and programmer resources. In this seminar, we'll look at techniques you should use when you write SAS code to minimize the use of CPU, I/O, memory, disk space, networking and programmer resources. We'll examine SAS coding techniques that produce identical results and compare the computer resource usage of each technique. We'll also look at some tricks of the trade to minimize code maintenance.
Excel VBA: When You Have to Step Outside SAS®
Instructor: Peter Eberhardt, Fernwood Consulting Group, Inc.
As SAS programmers and analysts, we are comfortable and at home in an environment where we have programs and commands that automate our processing. The data change - we simply rerun our code to produce consistent results.
However, when we have to work with data in Excel, whether cleaning up worksheets so they can be imported by SAS, or dressing up worksheets for management review. Many SAS programmers are operating in a manual, nonreplicable environment. The data change - we have to repeat all of the manual steps again. Needless to say, this is not only time-consuming, but also error-prone.
In this workshop you will learn how to use the programming language and environment that comes with Excel: Visual Basic for Applications (VBA). VBA is essentially a specialized subset of the Microsoft Visual Basic (VB) programming language. We will start with a comparison of the two programming environments: the SAS (or SAS® Enterprise Guide®) programming window and VBA code modules with an initial focus on the editor. From there, we will look at some of the differences in common programming constructs, such as DO loops and IF statements. Once we have looked at some of the fundamentals of the VBA language, we will start to look at how a program accesses the worksheet with a focus on a few main concepts:
- Locating cells.
- Moving through rows and columns.
- Identifying cell content.
- Acting on cell content.
- Adding or removing rows and columns.
After we understand some of the basics of accessing the data in the Excel spreadsheet, we will then see how to build and execute Excel functions to tie it all together. The workshop will wrap up with examples showing how to take formatted Excel reports and convert them into worksheets that can be easily read by SAS, followed by examples of taking SAS tabular output and creating formatted Excel reports.
The workshop will use Excel 2010 VBA for the examples, but all of the content will be applicable to earlier versions of Excel.
Innovative Tips and Techniques: Doing More in the DATA Step
Instructor: Art Carpenter, California Occidental Consultants
This course is designed to be taken by a student who has a basic understanding of the DATA step, its primary statements and its basic operation. The seminar will provide a short refresher of these basics, but will concentrate on topics that will allow the user to take full advantage of the power of the DATA step. In order for you to write innovative DATA step solutions to complex coding problems, it is necessary for you to have more than a basic understanding of the individual statements. You need to understand how the various statements interact with each other and how their options can be leveraged to provide the kind of DATA step code that will provide innovative solutions to the toughest of problems.
Topics will include:
- Data set options with impact.
- New functions and old functions with new options.
- Evaluating expressions.
- DATA step component objects ? hash tables.
- Transposing the data using arrays.
- Using the DOW loop.
- Using double SET statements effectively.
- Look-ahead and look-back techniques.
- Using multilabel formats to create running averages.
- Introduction to hashing.
SAS® Administration: Understanding Architecture and Administration
Instructors: Gregory S. Nelson, ThotWave Technology LLC and Gordon Cox, SAS
Since its debut in 2004, SAS®9 has raised the importance of a well-designed SAS environment and the role of information technology for successful SAS environments. From design and installation to management and monitoring, the role of the SAS administrator has risen to a state of prominence in most SAS shops.
The implementation of business analytics in any organization requires an integrated approach that bridges both IT and the business in a collaborative fashion. This workshop is designed to help both the IT professional understand SAS as well as the SAS programmer understand IT - and how SAS should be managed.
We will guide the participant through the various SAS client and server components and outline how SAS works. Using examples from SAS Enterprise BI Server, SAS Data Integration, SAS Data Quality, SAS® Scalable Performance Data Server® and SAS® Grid Computing, we'll turn concepts into reality through animations that highlight various SAS architectures in detail, show which parts of SAS have to be managed, and introduce best practices for monitoring and maintaining your SAS environment.
Workshop topics will include:
- SAS administration roles and responsibilities.
- Adoption of new technologies, including managing hot fixes and upgrades.
- System monitoring and performance and capacity planning.
- Managing metadata.
- Understanding security administration and roles.
- Best practices in data governance, architecture and business processes.
- Developing organizational competencies around BI and analytics, including creating a center of excellence.
The speaker is an expert in performance management, system design, and architecture and business integration.
12:30 - 4:00 p.m.
Building Powerful Reusable Tools with the SAS® Macro Language
Instructor: Kirk Lafler, Software Intelligence Corp.
The SAS macro language is a powerful feature for extending the capabilities of SAS. This course presents a collection of techniques for constructing reusable and effective macro tools. Attendees learn how to build functional macros that process statements containing SAS code; apply basic design principles in the development of reusable macro tools; create macros containing keyword and positional parameters; utilize defensive programming techniques; build a library of macro utilities; interface the macro language with the SQL procedure; and develop efficient and portable macro language code.
Creating Complex Reports
Instructor: Cynthia Zender, SAS
This seminar is for intermediate to advanced SAS programmers. We will investigate how eight complex reports were produced with SAS. All the code that produced the reports will be covered. All report output is produced using ODS (rather than LISTING) output. The reports to be covered include three versions of a standard demographic report, a color-banded report produced with PROC TABULATE, a report that uses special fonts (Bissantz SparkFonts) to produce a sparkline report, several graph examples, and several unique report ordering examples.
Procedures and topics to be covered include: REPORT, TABULATE, FORMAT, MEANS, FREQ, macro processing and DATA_NULL_ programming (as each component is used to produce the reports).
SAS® SQL: Building on the Basics
Instructor: Davetta Dunlap, SAS
Tracking the processing of queries can often help with debugging code and making performance improvements. Also, optimizing SQL queries, including join performance, is the goal of many SQL programmers. Do you know when you should consider implicit versus explicit SQL pass-through? Are you taking advantage of threading in your SQL programs? Have you ever used options such as SASTRACE= and_Method to track and optimize your queries? In this seminar, we will look at a variety of ways for you to monitor the processing and efficiency of your SQL queries and to fine-tune them to run more effectively. Basic SQL query knowledge is assumed.
SG (Statistical Graphics) Procedures and ODS GRAPHICS for the Nonstatistician
Instructor: Michele Ensor, 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 create 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 not covered in this seminar.) In addition, use of the ODS GRAPHICS statement for setting or changing graph options will be covered.
8:00 - 10:00 a.m.
Creating Statistical Graphics with ODS in SAS
Instructor: Warren F. Kuhfeld, SAS
Effective graphics are indispensable in modern statistical analysis. SAS 9.2 provides ODS Graphics, new functionality used by statistical procedures to create statistical graphics as automatically as they create tables. ODS Graphics is also used by new SAS/GRAPH® procedures that are designed for graphical exploration of data.
This tutorial is intended for statistical users and covers the use of ODS Graphics from start to finish in statistical analysis. You will learn how to:
- Request graphs created by statistical procedures.
- Use the new SGPLOT, SGPANEL, SGSCATTER and SGRENDER procedures in SAS/GRAPH to create customized graphs.
- Access and manage your graphs for inclusion in Web pages, papers and presentations.
- Modify graph styles (colors, fonts and general appearance).
- Make immediate changes to your graphs using a point-and-click editor.
- Make permanent changes to your graphs with template changes.
- Specify other options related to ODS Graphics.
SAS® Procedures for Analyzing Survey Data
Instructor: Pushpal Mukhopadhyay, SAS
The design of probability-based sample surveys involves specialized elements such as stratification, clustering and unequal weighting. In order to make statistically valid inferences, correspondingly specialized software is required that takes these elements into account in variance estimation.
This tutorial provides an overview of the basic functionality of the SAS/STAT® procedures, which are specifically designed for selecting and analyzing probability samples for survey data. You will learn how to:
- Select probability samples according to various designs with PROC SURVEYSELECT.
- Produce descriptive statistics from your sample with PROC SURVEYMEANS and PROC SURVEYFREQ.
- Build statistical models with PROC SURVEYREG, PROC SURVEYLOGISTIC and PROC SURVEYPHREG.
The tutorial also discusses the characteristics of different variance estimation techniques, including both Taylor series and replication methods.
The course is intended for a broad audience of statisticians who are interested in analyzing sample survey data. Familiarity with basic statistics, including regression analysis, is strongly recommended.
10:30 - 12:30 a.m.
Data Simulation for Evaluating Statistical Methods in SAS®
Instructor: Rick Wicklin, SAS
To assess statistical techniques, you often need to create data with known properties, both random and nonrandom. This workshop presents techniques for using the DATA step and SAS/IML® software to simulate data.
You will learn to simulate:
- Data from common univariate and multivariate distributions, including skewed and heavy-tailed distributions.
- Data from a mixture of distributions.
- Data with known properties such as a specific covariance structure or a known regression structure.
You will learn to use simulated data to evaluate:
- The performance of algorithms.
- The robustness of statistics.
- The coverage probabilities of approximate confidence intervals.
This workshop is intended for researchers and practicing statisticians.
Introduction to Bayesian Analysis Using SAS® Software
Instructor: Maura Stokes, SAS
Bayesian methods have become increasingly popular in recent years in a number of different disciplines. This tutorial provides an introduction to Bayesian methods with applications in the areas of the generalized linear model and survival analysis.
The first part of the course provides an overview of Bayesian methodology, including motivation and Bayesian inference, as well as computational methods and convergence diagnostics relevant to the SAS implementation. The second part of the course discusses applications using new capabilities in SAS/STAT software in the GENMOD, LIFEREG and PHREG procedures, which are based on Gibbs sampling. Examples will include methods such as linear regression, logistic regression, Poisson regression, Cox regression, parametric survival models and the piecewise exponential model.
A master's-level knowledge of statistics is assumed as well as experience with generalized linear models and survival analysis. Previous exposure to Bayesian methods is useful but not required.