To register, please send email to researchservices@bc.edu with the names of the tutorials that you are interested in attending. 

Demographic analysis with ArcGIS

The focus of this workshop will be on the use of ArcGIS to analyze demographic data. The session will highlight GIS data available for research and include demonstrations of ArcGIS using cases based on Census and related data. GIS is an analysis tool which complements other quantitative methods used to analyze population data. The data that the Census Bureau collects during the decennial census and other population surveys has grown extensively over the years and has become an important resource for researchers and government agencies. Besides providing the basis for congressional redistricting, Census data are used in many other ways. Since 1975, the Census Bureau has had responsibility to produce small-area population data needed to redraw state legislative and congressional districts. Other important uses of Census data include the distribution of funds for government programs; planning the right locations for schools, roads, and other public facilities; helping real estate agents and potential residents learn about a neighborhood; and identifying trends over time that can help predict future needs. Most Census data are available for many levels of geography, including states, counties, cities and towns, ZIP codes, census tracts and blocks.

Census data and GIS applications are used by community planners, marketing, managers, scientists and researchers in education, economists, sociologists, social workers, health care managers, librarians, and data administrators.

International population data are available also to address demographic issues in a specific country, at regional or at global scale. We will discuss these resources with those interested. No prior knowledge of ArcGIS is required.

2:00 - 4:00  January 31, 2008 Gasson 9

Introduction to ArcGIS

Geographic Information Systems (GIS) are used today to analyze and represent data with geographical reference on maps. It is widely used in academia, private industry and government agencies and the number of applications is increasing. ArcGIS Desktop software products from the Environmental Research Systems Institute (ESRI).

ArcGIS Desktop is an integrated suite of advanced GIS applications and interfaces, including ArcMap, ArcCatalog, ArcGlobe, ArcScene, ArcToolbox, and ModelBuilder. Using these applications and interfaces, you can perform any GIS task, from simple to advanced, including mapping; geographic analysis; data editing, compilation, and management; visualization; and geoprocessing. ArcGIS Desktop is scalable to meet the needs of many types of users.

This session will introduce users to: 1) GIS software, data and technical support at Boston College; 2) License options; 3) Main ArcGIS features and capabilities (ArcMap, ArcCatalog, ArcTool, ArcGlobe); 4) Present available extensions and capabilities (Spatial Analyst, Geostatistical Analyst, etc); 5) Demos using Census data; Demos using Environmental data. Options to get data and training will be also discussed.

2:00 - 4:00 January 24, 2008 Gasson 9

Introduction to Linux

 This tutorial provides an introduction to Linux.  This tutorial demonstrates basic Linux/Unix commands to get you started with Linux/Unix.  No previous knowledge of Linux/Unix is required.

2:00 - 3:30 March 14, 2008  Gasson 9

Introduction to the Linux Cluster

The Linux cluster at Boston College consists of 26 compute nodes connected by fast Ethernet. Each node has 2 dual core 2.6GHz AMD Opteron processors. This tutorial discuss:

• Hardware
• Compilers
• The queues and running a job
• Optimization
• Software, including Stata, Matlab, NAMD, Gromacs, ACML.

2:00 - 3:30 March 28, 2008 Gasson 9

Introduction to Mathematica

The goal of this hands–on seminar is to introduce beginning level users to Mathematica computing system. No previous experience with Mathematica is necessary, while some background in Calculus and Algebra will be helpful. The software is now used worldwide in academia, industry and government research labs and has a complete environment for technical computing tasks, whether simple calculations or large-scale computations, complex programming, visualizing or modeling data. Boston College has a site license and many faculty, staff and students are using Mathematica for research, teaching and learning. We will demonstrate topics related to use of documentation, help, notebooks, Mathematical functions, Visualization and Graphics, and new capabilities in Mathematica 6.0.

2:00 - 4:00 February 7, 2008 Gasson 9

Introduction to MPI

MPI stands for Message Passing Interface and is the de facto
programming interface for message-passing on a parallel machine.  This tutorial
will cover basic functions in MPI programming:

• Basic communication functions
     1) point-to-point communication
     2) collective communication
• Advanced communication functions
• Communicator

 2:00 - 3:30 April 4, 2008 Gasson 9

Introduction to Nvivo7

This workshop provides an introductory demonstration of how to use Nvivo7 for qualitative analysis. Nvivo7 can be used to eliminate the problems of managing large amounts of qualitative data, can be used to code and re-code qualitative data, keep an audit trail of the analysis process, and supports both individual researchers and research teams in discussing coding and analysis issues. This course is intended for beginning and intermediate users who have had some exposure to the methodologies and theories of qualitative analysis.

 This workshop will be given in a demonstration (non-hands on) format:

• Getting started with Nvivo7
• Thinking about qualitative research design
• Source Preparation
• Attribute Variables
• Data importing and data analysis examples
• Comparison with other qualitative research packages such as HyperResearch and Atlasti

2:00 to 3:30 January 30, 2008,  Gasson 9

Introduction to OpenMP

OpenMP is a programming model standard for shared memory machines. It is the ideal programming method for developing portal multi-threaded programs.  This tutorial will cover:

• Parallel regions
• Work sharing
• Data environment
• Synchronization
• Runtime functions

2:00 - 3:30 April 11, 2008 Gasson 9

Introduction to Stata 1

Stata is a powerful and yet easy to use statistical package. This hands-on tutorial is designed as an introduction for beginning users who are just getting started using Stata. The following topics will be covered:

• Overview of Stata, including how Stata compares to the other most popular statistical packages and special features of Stata.
• Getting started with Stata.
• Creating and using "log" files.
• Working with Data in Stata.
• Stata graphs.

12:00-1:30 February 7, 2008 Gasson 9

Introduction to Stata 2

This hands-on tutorial is designed as an introduction for beginning users who knows basics of Stata. The following topics will be covered:

• Creating and using "do" files
• Discuss simple regression models and significance tests.
• Writing loops.

12:00-1:30 February 21, 2008 Gasson 9 

Locating and Using Data for Secondary Research at Boston College

 Boston College offers many sources and repositories of data for secondary research in the social sciences, education, nursing, economics, business and other disciplines.  This workshop is particularly geared to researchers who need to access, analyze and manipulate data from BC's subscription data repositories.  This tutorial will help  you: find the data you need for your research or class project; learn about the Boston College collection of data  resources in the Statistical Data Catalog; and how to download the data onto your desktop, including how to import  into quantitative analytical tools such as SPSS.  Get a tour of the Inter-University Consortium for Political and Social Research, a data archive that includes over 5,000 datasets. We will also discuss the library’s guides to key Business, Economics, Education, Health, and General U.S. and cross-national data sources. Topics may be customized based on attendees’ research interests.

2:00 - 3:30 February 6, 2008 Gasson 9

MATLAB 1: Introduction to Matlab programming

MATLAB fundamentals provide a working introduction to the MATLAB technical computing environment. Matlab can be used with all aspects Mathematical computation, analysis, visualization, and algorithm development. This course is intended for beginning and intermediate users. No prior knowledge of MATLAB is required. Familiarity with a programming language (Fortran, C for example) will be helpful. Themes of vector and matrix data analysis, graphical visualization, data modeling, and MATLAB programming are explored in the context of realistic examples. 

This Matlab hands-on practice workshop will present:

• Introduction: The Matlab system; Matlab documentation and help; Starting and quitting Matlab; How to use Matlab on Linux cluster “scorpio”
• Matrices and arrays:  Entering matrices; Load data; Matrix Algebra
• Matlab programming: Program control statements; Data types; Variables; Operators; Expressions; Matlab functions; Creating a program; Importing and exporting text and Excel data
• Introduction to Matlab graphics capabilities

2:00 - 4:00 February 14, 2008 Gasson 9

MATLAB 2: Graphs and Visualization

The type of graph needed in a specific project depends on the nature of available data and on what is intended to reveal about the data. MATLAB predefines many graph types,  such as line, bar, histogram, and pie graphs. There are also 3-D graphs, such as surfaces, slice planes, and streamlines.  There are two basic ways to create graphs in MATLAB: 1) Use plotting tools to create graphs interactively; 2) Use the command interface to enter commands in the Command Window or create plotting programs (m files).

This Matlab hands-on practice workshop will focus on m-files to produce graphics, data visualization, and animation. We will show:

• Basic Plotting Commands: Commands Plotting Steps; Creating Line Plots
  Specifying Line Style; Colors, Line Styles, and Markers; Specifying the Color and Size of Lines; Adding Plots to an Existing Graph; Plotting Only the Data Points; Plotting Markers and Lines; Line Styles for Black and White Output; Samples of various 2D plots
• Figure Windows: Displaying Multiple Plots per Figure; Subplots; Save and print plots
• Samples of 3D Plots
• Animation:  Movies; Erase Modes; Examples on how to create animations

Examples presented (m files) can be easily modified and applied to your specific  experimental or model data.

 2:00 - 4:00  pm, February 21, 2008, Gasson 9

MATLAB 3: Statistics

This MATLAB hands-on practice workshop with focus on statistical toolbox and illustrate some of the methods used in univariate and bivariate statistics. The objective is to learn to work with data in the MATLAB environment, compute basic descriptive statistics, and visualize data in a variety of ways. It is assumed that participants have already some knowledge of  MATLAB  (at the level of previous two workshops) and background in Applied Statistics.

• Descriptive statistics: Measures of center, spread, and shape
• Statistical plotting: Histograms, scatter plots, and box plots
• Review the basics of probability and random variables and explore the variety of probability distributions available in the Statistics Toolbox. Random variables, Sampling distributions, Bootstrapping
• Explore regression analysis for bivariate data: Regression concepts,
  Linear and nonlinear models, Scatter plots
  Correlation and covariance
• Linear least squares.  Polynomial fitting.  Graphical user interface tools for linear regression

2:00 - 4:00 February 28,  2008,  Gasson 9

MATLAB 4: Multivariate statistics

This MATLAB hands-on practice workshop with focus on and multivariate statistics.  The objective is to learn to work with data in the MATLAB environment, to perform statistical analysis of data sets with multiple variables. One of the difficulties inherent in multivariate statistics is the problem of visualizing data that has many variables. Fortunately, in data sets with many variables, groups of variables often move together. One reason for this is that more than one variable might be measuring the same driving principle governing the behavior of the system.  When this happens, you can take advantage of this redundancy of information. You can simplify the problem by replacing a group of variables with a single new variable. Principal components analysis is a quantitatively rigorous method for achieving this simplification.

Topics illustrated:

• Principal Components Analysis (including the Principal Component Coefficients, the Component Scores, the Component Variances,  Visualizing the Results of a Principal Components Analysis)
•  Factor analysis.
• Multivariate regressions and special graphics methods to visualize the relationships between many variables.

It is assumed that participants have already some knowledge of  MATLAB  (at the level of previous workshops) and background in Applied Statistics.

2:00 - 4:00  March 20, 2008  Gasson 9

Matlab 5: Optimization techniques

 Optimization Toolbox extends the capability of the MATLAB numeric computing environment. The toolbox includes routines for many types of optimization including: Unconstrained nonlinear minimization;  Constrained nonlinear minimization, including goal attainment problems; Minimax problems, and semi-infinite minimization problems; Quadratic and linear programming; Nonlinear least-squares and curve fitting; Nonlinear system of equation solving; Constrained linear least squares; Sparse and structured large-scale problems.

The workshop will illustrate the strategy to identity the algorithm for a given problem. Examples include: finding minimum with constraints; nonlinear least square fit of observational data, and solving nonlinear equations.

It is assumed that participants have already some knowledge of MATLAB and Linear Algebra.

2:00 - 4:00  March 27, 2008  Gasson 9

Matlab 6: Ordinary differential equations

 Ordinary differential equations (ODE) are used in mathematics, science and engineering to describe how physical quantities change in time. Modern applications are found in many research fields: dynamic systems, physics, evolutionary biology, chemical kinetics, environmental sciences, economics, to mention just a few. The ODE solvers are designed to handle ordinary differential equations. An ordinary differential equation contains one or more derivatives of a dependent variable with respect to a single independent variable, usually referred to as time.

We will illustrate Matlab solvers with realistic examples or ODE with initial value conditions (also  known as initial value problems), with focus on problem formulation, numerical solution accuracy, methods of solution exploration, valuable especially for nonlinear problems.

It is assumed that participants have already some knowledge of MATLAB, Linear Algebra, ODE theory,  and numerical analysis.

2:00 - 4:00  April 3, 2008  Gasson 9

Parallel computing using Matlab with Star-P

This seminar introduces Matlab users to Star-P, which can accelerate Matlab codes, especially long running Matlab codes in research projects. Examples will be shown on how to run Matlab on the Scorpio Linux Cluster, and how to use Star-P to speed up your Matlab codes. We will demonstrate data and task parallel calculations and the role of vectorization in improving code performance. We will compare the performance of Matlab codes run on one processor, versus Star-P version of the code run on several processors. Familiarity with Matlab, Applied Mathematics and UNIX are needed.  We will discuss also projects of interest for your research that could benefit by the use of Star –P with Matlab.

2:00 - 4:00 April 17, 2008  Gasson 9

SAS 9.1.3 FOR WINDOWS

SAS is a powerful and complex statistical analysis package. This hands-on tutorial is designed as an introduction for beginning users who are just getting started using SAS on Windows or a refresher for those who have not used SAS for awhile. The following topics will be covered:

• Overview of SAS, including how SAS compares to the other popular statistical packages. We will discuss  special features  and advantages/ disadvantages of using SAS.
• Getting started with SAS
• Working with Data in SAS
• Using SAS for descriptive statistics, simple regression models, and significance tests
• Intro to SAS Graph
• Discuss other SAS modules and resources

2:00 - 3:30 February 20, Gasson 9