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Conference Tutorials

Take advantage of additional training opportunities offered before and after SAS Global Forum. The tutorials listed below are extra-fee events and include relevant handouts. When you register for the conference, you can select the tutorials you want to attend.

For the first time, SAS Global Forum Tutorials are open to the public! If you are unable to attend the conference, you can still take advantage of the tutorials. Non-conference attendees must register for the tutorials and there is a $35 fee per tutorial in addition to the cost.

Pre-Conference – Sunday, March 23

8:00 am - 10:00 am
(concurrent offerings)
$75.00 each

10:30 am - 12:30 pm
(concurrent offerings)
$75.00 each

Introduction to Logistic Regression

 

Advanced Logistic Regression

Getting Started with Time Series Data and Forecasting in SAS®

 

Power and Sample Size Computations

8:00 am - 11:30 am
(concurrent offerings)
$155.00 each

12:30 pm - 4:00 pm
(concurrent offerings)
$155.00 each

Cleaning, Validating, and Reshaping Your Data: Taking Advantage of SAS Tools

 

Creating Statistical Graphics in SAS

Demystifying SQL

 

Model Selection with SAS/STAT® Software

Creating Graphs and Reports in SAS® Enterprise Guide®

 

Finding the Gold in your Data: An Overview of Data Mining Techniques

The Role of the SAS Administrator: A Day in the Life of a Modern SAS Enterprise

 

Optimizing Big Data Programs

 

Understanding Why Your Macros Don’t Work

 

Using Master Data Management to Improve Data Quality and Accuracy

Post-Conference – Wednesday, March 26

1:30 pm - 4:30 pm
(concurrent offerings)
$155.00 each

Building Dynamic Programs and Applications Using the SAS® Macro Language

Introduction to Social Network Analysis

Reporting Your Way – ODS LAYOUT and the Report Writing Interface are Now Production!

Details

Advanced Logistic Regression
Maura Stokes, Senior R&D Director, Advanced Analytics Division, SAS
Cost: $75.00
Level: Intermediate/Advanced; A strong working knowledge of binary logistic regression is assumed.
Logistic regression, generally used to model dichotomous response data, is one of the basic tools for a statistician. But what do you do when maximum likelihood estimation fails or your sample sizes are questionable? What happens when you have more than two response levels? This tutorial briefly reviews logistic regression for dichotomous responses, and then illustrates alternative strategies for the dichotomous case and additional strategies such as the exact logistic regression, proportional odds model, partial proportional odds model, generalized logit model, and conditional logistic regression. The presentation is based on the third edition of the book Categorical Data Analysis Using SAS by Stokes, Davis and Koch (2012).

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Building Dynamic Programs and Applications Using the SAS® Macro Language
Art Carpenter, California Occidental Consultants
Cost: $155.00
Level: Advanced
This seminar shows you how to take advantage of SAS Macro Language capabilities that enable you to write dynamic programs and applications. By mastering the concepts and techniques presented in this class, your programs will become free of hard-coded data dependencies, thus eliminating the need to re-write the code every time a data set name, variable name or other data attribute changes. Let “them” change the project's specifications as often as “they” want – your code is ready!

The dynamic programming techniques that you will learn about during this seminar:

  • Are flexible and are easily adaptable to changing data structures, data table names and variable (field) attributes.
  • Reduce maintenance requirements by removing data dependencies from within the programs.
  • Provide significant resource savings during program/application development cycles.
  • Gives the end user extensive control over program execution by using tables such as SAS data dictionaries, SAS data sets and Excel tables.
  • Reduce program validation efforts by providing reusable and generalized code that can be applied to many different applications.
  • Establish controlled data environments, thus insuring data integrity throughout your organization.

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Cleaning, Validating and Reshaping Your Data: Taking Advantage of SAS Tools
Art Carpenter, California Occidental Consultants
Cost: $155.00
Level: Intermediate/Advanced
The procedures of SAS along with the DATA step provide the programmer and data analyst access to flexible programming power unavailable in any other programming language. Along with that power comes the complexity of multiple solutions to many common programming tasks. This class covers a number of intermediate and advanced SAS programming topics, offering solutions that take advantage of techniques not employed by most SAS programmers. Based on Carpenter’s latest book, Carpenter’s Guide to Innovative SAS Techniques, published in the spring of 2012, this course will extend the knowledge and tool set of SAS programmers that work with data.

During this seminar we will:

  • Learn to create user-defined formats and functions to clean and validate your data.
  • Extend PROC COMPARE with the Macro Language to automate data comparisons.
  • Explore alternative techniques to PROC TRANSPOSE when reshaping your data.
  • Discover how to display and report on all levels of classification variables, even when they are not in the data.

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Creating Graphs and Reports in SAS Enterprise Guide
Stacey Syphus, Instructor and SAS Enterprise Guide Curriculum Team Lead, SAS
Cost: $155.00
PROC TABULATE and SAS/GRAPH® procedures are an extremely powerful part of the SAS programming language, but it can be challenging code to write – even for the most veteran programmers. In this seminar, you will see how point-and-click tasks and wizards in SAS Enterprise Guide can be used to create customized summary reports, bar charts and map graphs – even if you don’t know anything about SAS code at all! Behind the scenes PROC TABULATE, GCHART and GMAP code is generated for you. You also see how to enhance reports and graphs by using task options and modifying the generated SAS code.

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Creating Statistical Graphics in SAS
Warren Kuhfeld, R&D Director, Advanced Analytics Division, SAS
Cost: $155.00
Level: Beginner; No prior experience with ODS Graphics is assumed.
Effective graphics are indispensable in modern statistical analysis. SAS provides statistical graphics through ODS Graphics, functionality that is used by statistical procedures to create statistical graphics as automatically as they create tables. ODS Graphics is also used by a family of Base SAS procedures designed for graphical exploration of data.

This tutorial is intended for statistical users and covers the use of ODS Graphics from start to finish. You will learn how to:

  • View graphs created by statistical procedures.
  • Make immediate changes to your graphs using a point-and-click editor.
  • Make permanent changes to your graphs with template changes.
  • Use the SGPLOT, SGPANEL, SGSCATTER and SGRENDER procedures to create a wider variety of statistical graphs.
  • Use the SGPLOT procedure to create sophisticated modern graphs consisting of multiple graphical components.
  • Access and manage your graphs for inclusion in Web pages, papers and presentations.
  • Modify graph styles (colors, fonts and general appearance).

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Demystifying SQL
Christianna Williams, Independent Consultant
Cost: $155.00
Level: Intermediate
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 semicolons 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 seminar is a sort of PROC SQL “boot camp” and 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!

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Finding the Gold in Your Data: An Overview of Data Mining Techniques
Dave Dickey, William Neal Reynolds Distinguished Professor of Statistics, North Carolina State University
Cost: $155.00
Level: Intermediate
This course consists of an introduction to the main techniques in data mining. It is structured around paper 501-2013 from the 2013 SAS Global Forum and provides deeper insights into the main components of SAS® Enterprise Miner™. It includes demos of the basic techniques available in this data mining tool. Main topics include decision trees, regression trees, neural networks, logistic regression, association analysis, text mining and clustering. Rather than a detailed mathematical approach, this is an introductory overview of the tools available with examples to illustrate the concepts.

The course is at an intermediate level statistically only in that familiarity with basic statistical ideas will help in interpreting and appreciating the results that will be shown. In terms of SAS, it is at an elementary level. It does not require SAS programming knowledge beyond a very elementary level and in fact should be accessible even to those with little or no programming experience. It is meant as an introductory overview tour of the SAS Enterprise Miner suite of analytics.

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Getting Started with Time Series Data and Forecasting in SAS
Kenneth Sanford, Econometric Evangelist, Advanced Analytics Division, SAS
Cost: $75.00
Level: Beginner; No prior knowledge about time series is necessary. Familiarity with the DATA step and linear regression is assumed.
Many analysts deal with time series data on a daily basis. This tutorial focuses on how to work with them productively. In the first part of the tutorial, you will learn how to turn transactional data into a time series effectively. Next, the focus turns to basic forecasting techniques that use past fluctuations to predict future events. This modeling technique will then be extended to include explanatory factors in the prediction equation.

Econometrics modeling is not limited to forecasting techniques. The second part of the tutorial reviews how to use observational data to estimate causal effects. Many of these methods involve the use of panel data, which is the intersection of time-series and cross-sectional data. The tutorial concludes with an examination of how to use these models in “what-if” analysis for such problems as optimal pricing.

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Introduction to Logistic Regression
Maura Stokes, Senior R&D Director, Advanced Analytics Division, SAS
Cost: $75.00
Level: Beginner; A working knowledge of linear regression is required.
Logistic regression is one of the basic modeling tools for a statistician or data analyst. This tutorial focuses on the basic methodology behind logistic regression and discusses parameterization, testing goodness of fit, and model evaluation using the LOGISTIC procedure. The tutorial concentrates on binary response models, but direction for handling ordinal responses is also provided. This tutorial discusses numerous ODS graphics now available with the LOGISTIC procedure, as well as newer features of SAS such as ROC comparisons and odds ratios with interactions. The tutorial includes numerous examples.

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Introduction to Social Network Analysis
Rich LaValley, SAIC, and Dominick Wright, Institute for Defense Analyses
Cost: $155.00
Level: Intermediate/Beginner in Social Network Analysis; Strong understanding of the macro language
The workshop is aimed at researchers who are new to social network analysis (SNA) and would like to understand whether and how they can use it in their work place. The goal of the workshop is to provide attendees with basic insight into SNA and how it can be used in business applications. Multiple examples will be provided to illustrate several key ways of how to use SNA. Although the workshop does not focus on any specific software or data handling tool, it offers an opportunity for participants to have a first practical experience of how to use social network data, draw graphs, and perform some simple calculations and analyses using SAS’ SNA tool. There are some simple computer-based exercises for a hands-on illustration of how to visualize different types of network data and how to compute basic metrics and indicators.

Participants will learn:

  • Fundamental principles of SNA.
  • Some essential technicalities: collection methods, format and properties of network data.
  • Opportunities and challenges arising from the increasing availability of social network data.
  • Use of visualization and how they support network data interpretation.
  • Basic measures of social network analysis, composition and structure, how they can be used to uncover important aspects under study and how they can be represented graphically.
  • How SNA can be successfully integrated into research and business applications.
  • Recommended book to learn more about SNA.

Requirements: Participants are assumed to have no previous knowledge of social network analysis.
Learning Outcomes: The workshop will provide attendees with a basic insight into social network analysis and how it can be used in their business.

This course makes extensive use of example macros that have been gathered from real-world applications, and it concentrates on the techniques necessary to make effective use of these tools.

Intended Audience Level: Strong understanding of the macro language

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Model Selection with SAS/STAT Software
Funda Gunes, Senior Research Statistician, Statistical Applications Division, SAS
Cost: $155.00
Level: Intermediate/Advanced; Requires an understanding of basic regression techniques
When you are faced with a predictive modeling problem that has many possible predictor effects – dozens, hundreds or even thousands – a natural question is, "What subset of the effects provides the best model for the data?"

This tutorial explains how you can address this question with model selection methods in SAS/STAT software for linear and generalized linear models. The tutorial also explores the practical pitfalls of model selection, including issues which have led experts to criticize the validity of some methods. This tutorial focuses on applications of the GLMSELECT procedure, but it also features the new HPGENSELECT procedure for generalized linear models.

You will learn how to use the following approaches:

  • Model selection diagnostics, including graphics, for detecting problems.
  • Use of validation data to detect and prevent under-fitting and over-fitting.
  • Modern penalty-based methods, including LASSO, adaptive LASSO and elastic net as alternatives to traditional methods such as stepwise selection.
  • Bootstrap-based model averaging to reduce selection bias and improve predictive performance.
  • Selection for nonparametric models with spline effects.
  • Model hierarchy among effects.

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Optimizing Big Data Programs
Christine R. Riddiough, Principal Technical Training Consultant, SAS
Cost: $155.00
Audience: SAS programmers who have attended the SAS Programming 2: Data Manipulation Techniques course or who have a strong knowledge of indexing, array processing and the use of formats. Some experience working in the SAS BI environment is needed.
This seminar will review traditional SAS techniques for optimizing programs that require table lookups. We will do this by focusing on in-memory techniques. The techniques discussed will include:

  • Arrays (one-dimensional and multi-dimensional).
  • Hash objects.
  • Formats.

We will look at indexing as a means of “super-charging” your lookups and sampling for the purpose of exploring your data. We will also investigate several newer features in SAS as a way to optimize your programs in a BI environment, including grid computing and the use of PROC SCAPROC to help “gridify” your programs.

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Power and Sample Size Computations
John Castelloe, Senior Research Statistician Developer, Advanced Analytics Division, SAS
Cost: $75.00
Level: Beginner; Prior exposure to power and sample size computations is assumed.
Power determination and sample size computations are an important aspect of study planning and help produce studies with useful results for minimum resources. This tutorial reviews basic methodology for power and sample size computations for a number of analyses including proportion tests, t tests, confidence intervals, equivalence and noninferiority tests, survival analyses, correlation, regression, ANOVA, and more complex linear models. The tutorial illustrates these methods with numerous examples using the POWER and GLMPOWER procedures in SAS/STAT software as well as the Power and Sample Size Application. Learn how to compute power and sample size, perform sensitivity analyses for other factors such as variability and type I error rate, and produce customized tables, graphs and narratives. Special attention will be given to the newer power and sample size analysis features in SAS/STAT software for logistic regression and the Wilcoxon-Mann-Whitney (rank-sum) test.

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Reporting Your Way – ODS LAYOUT and the Report Writing Interface are Now Production!
Pete Lund, Looking Glass Analytics
Cost: $155.00
Level: Intermediate
I have a passion for reporting – more specifically, a passion for reporting using SAS. For those of us who love developing reports, SAS 9.4 brings exciting news. Two powerful features, which have been available in some form for quite a while, are finally considered production: ODS LAYOUT and the Data Step Report Writing Interface. These open up a whole new world of flexible report design and development.

As the name implies, ODS LAYOUT allows you to “layout” the page for placement of multiple output objects. The output objects can be the results of any procedure or data step that produces output. With “gridded” LAYOUT you specify row and column information, and the output goes into those “cells.” In “absolute” LAYOUT you specify the actual size and location of regions on the page and the output that goes into those regions.

If you can’t get exactly what you want from PROC REPORT or TABULATE, the Report Writing Interface comes to the rescue. The Report Writing Interface is just a fancy way of saying you’re using the ODSOUT object in a data step. This object allows you to layout the page, create tables, embed images, add titles and footnotes and more – all from within a data step, using whatever data step logic you need. Also, all the style capabilities of ODS are available to you so that your data step created output can have fonts, sizes, colors, backgrounds and borders to make your report look just like you want.

This seminar will cover the basics of both of these new features. Examples will be based on “real-world” reports – the kind that makes people ask, “You did that report in SAS?” No longer do you have to tremble a bit when someone sends you a document or spreadsheet with their desired report mockup. Most likely, you’ll be able to meet their demands and maybe even improve on it. Course notes will be provided, and example code and data will be available for download.

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The Role of the SAS Administrator: A Day in the Life of a Modern SAS Enterprise
Gregory S. Nelson, ThotWave Technologies, LLC
Cost: $155.00
Level: Beginner/Immediate
The role of professional SAS administrator is turning 10 years old! Up until SAS®9, the systems manager was usually responsible for installation and the annual update of the license file but had little to no interaction with how people actually used the software. Today’s modern SAS administrator spends her day in architecture discussions, strategic planning, monitoring and yes, applying maintenance updates. As the role of the SAS administrator expands, so does the need to understand SAS solutions and what they might mean for their fit and function within the modern enterprise.

In this workshop, attendees will learn best practices in the various roles of a SAS administrator: strategy, architecture, installation, monitoring, maintenance and support. We will explore this in the context of the evolving SAS solutions, including SAS Data Quality, SAS Master Data Management, SAS Visual Analytics and SAS Business Intelligence, as well as analytic solutions such as forecasting and data mining. Topics will also include discussions of Hadoop, cloud, multi-tenet architectures, SAS grid and storage technologies. Students will be left with printed course materials along with links to all the animations that will serve them in their discussions back in their own organizations.

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Understanding Why Your Macros Don’t Work
Michelle Buchecker, Director, Education Division, SAS
Cost: $155.00
Level: Some macro knowledge recommended before attending this seminar.
This brain-teasing seminar will discuss the behind-the-scenes workings of the macro facility. The discussion also explains why:

  • Those macro variables you thought would resolve don't.
  • You need an extra period or four after a macro variable reference.
  • You need to understand the difference between %LET and CALL SYMPUT.
  • Those extra ampersands are necessary.

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Using Master Data Management to Improve Data Quality and Accuracy
Kari Richardson, Manager, Education Division, SAS
Cost: $155.00
Audience: Data quality stewards
Good quality data and analytics is the key to strategic business planning and decision making. But in a single organization, data can come from many different sources and is often not stored in a way that it can be shared across the organization. With SAS Master Data Management (MDM) solutions, businesses are provided with a single, accurate and unified view of data across their organizations. This seminar will discuss how SAS MDM solutions can:

  • Help you get to know your customers better.
  • Help you retain your customers.
  • Provide quality data and entity resolution.
  • Control the quality and usability of corporate data through data governance processes.

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