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Spring 2016 Tutorials

Information Technology Services

Research Services offers tutorials and workshops on a variety of topics.  Each semester, we present a series of tutorials.  If you have suggestions, please contact us (  We will also give customized tutorials, and we are  available for advanced topics and consulting. 

The tutorials are available to all members of the BC community.  There is no cost for the tutorials.

To register, please go to our on-line tutorial registration page at:  You will be asked to sign in using your BC username and password to register.  You can also use this web page to change the tutorials you signed up for.  You can also register by sending mail to with the names of the tutorials that you are interested in attending.

Please note that the locations of the tutorials varies.

The Spring 2016 Tutorials are:

MATLAB 1: Introduction to MATLAB programming Jan 22 11:00 - 12:30 O'Neill 245
SAS Programming I Jan 25 12:00 - 2:00 O'Neill 245
Introduction to Regression Jan26 12:00 - 1:30 O'Neill 246
Introduction to Multi-Level Modeling Jan 27 12:00 - 1:30 O'Neill 246
MATLAB 2: Graphs and Visualization Jan 29 11:00 - 12:30 O'Neill 245
SAS Programming II Feb 1 12:00 - 2:00 O'Neill 245
Introduction to R Feb 2 12:00 - 1:30 O'Neill 246
Statistical Data Conversion Feb 4 12:00 - 1:00 O'Neill 245
Introduction to Stata 1 Feb 5 11:30 - 1:00 O'Neill 245
Creating Web-Based Surveys with QUALTRICS Feb 9 12:00 - 1:30 O'Neill 246
Introduction to Qualitative Analysis Using NVIVO 11 Feb 10 12:00 - 1:30 O'Neill 246
Modern Statistics Methods Journal Club: The Elements of Statistical Learning from Data. Feb 11, Mar 17, Apr 22 TBA
Introduction to GIS Feb 12 10:00 - 11:30 O'Neill 307
Introduction to BC's Linux Cluster Feb 16 12:00 - 1:30 O'Neil 246
Introduction to Stata 2 Feb 18 12:00 - 1:30 O'Neill 245
Locating and Using Data for Secondary Research at Boston College Feb 23 12:00 - 1:30 O'Neill 307
Primary Data Collection: best practices for researchers Mar 1 10:30 - 12:00 O'Neill 246
Introduction to REDcap Mar 1 12:00 - 1:30 O'Neill 246

Creating Web-Based Surveys with QUALTRICS

Qualtrics offers a fairly intuitive Graphical User Interface to create complex surveys without complicated programming or coding.   Qualtrics offers extensive documentation, free online tutorials, an extensive library of surveys and options for encryption and anonymity, and excellent customer support. Strength of Qualtrics is its panel feature for repeated polling, built in social media sharing functions, and accessibility checker. Working within pre-defined templates, you
can use many different types of questions, including text, multiple checkboxes, sliders, single-answer radio buttons, and Likert scales.  Qualtrics offers extensive branching functionality.

Once the survey is completed, data can be downloaded into a format that can be used with a variety of quantitative and qualitative analysis programs. Qualtrics also offers foreign language functionality.

This tutorial will demonstrate how to create a survey in Qualtrics and also include a section on research protections and informed consent with respect to online survey development, distribution, and analysis.

BC community members who do not already have a Qualtrics account may contact for a Qualtrics account. Please note the Boston College School with which you are affiliated.

February 9, 2016 12:00 - 1:30 pm O’Neill 246

Introduction to BC's Linux Cluster

This tutorial is intended to be an introduction to the Linux cluster at Boston College. An overview, the primary components, philosophy, how to connect and apply BC’s Linux cluster will be presented.  Currently we have a cluster named Pleiades available. This hands-on tutorial covers the following topics:

  • Overview of  Linux cluster system at Boston College
  • The hardware/software architecture 
  • Management of Linux Cluster
  • How to set your local machine and access of BC clusters
  • Linux, PBS queuing system common commands
  • Basic Linux commands
  • How to submit jobs to clusters
  • Compile, debug and run programs

Febuary 16, 2016 12:00 - 1:30 pm O'Neil 246

Introduction to Geographic Information Systems

Geographic Information Systems (GIS) are used for visualizing, managing, creating, and analyzing geographic data. Such applications are widely used in academia, private industry and government agencies. Available GIS technologies are used to perform various tasks, from simple to advanced, including:  mapping, geographic analysis, geostatistics, data editing, compilation, management and visualization.

This session will introduce users to: 1) GIS data and technical support at Boston College; 2) Examples and demos using Census and Environmental data; 3). Options to get data and training will be also discussed. No prior knowledge of GIS is required.

February 12, 2016 10:00 - 11:30 am O’Neill 307

Introduction to Multi-Level Modeling

Mixed modeling, also known as multi-level modeling or sometime hierarchical linear modeling, is an essential tool in many research areas.  In biomedical research most designs are longitudinal, in social sciences there are often clusters of data such as students within classrooms within schools.  Many familiar methods such as ANOVA or regression assume that all observations are recorded independently.  Having clusters of correlated data violates this assumption and makes these methods invalid.  Mixed Modeling is an extension of regression that allows us to correctly model correlated data.  This tutorial is designed to give an introduction to linear mixed modeling.  We will focus on situations and designs where these methods are required, the dangers of using the wrong methods, and interpretation of the results that are standard across most statistical software packages.

January 27, 2016 12:00- 1:30 pm  O’Neill 246

Introduction to R

R is widely used  free statistical  software. To take advantage of R’s flexible output and graphics, packages are actively being developed to that interface R with other programs such as M-plus.  The rapid growth of R means that knowledge of this software will be essential to researchers doing complex statistical analysis.  This tutorial will explain how to download and install R (it’s free!!), learn basic operations.  We will focus on a couple concrete examples so that attendees will get familiar with the R environment.

February 2, 2016 12:00 - 1:30 pm O’Neill 246

Introduction to REDCAP (Research Electronic Data CAPture)

This tutorial is geared towards Boston College Principal Investigators, researchers and research project team managers. REDCap stands for Research Electronic Data Capture. REDCap is a web based, data collection, database management system that was originally developed at Vanderbilt University, initially for medical research. REDCap is now overseen by a consortium of academic research partners in the United States and throughout the world. Boston College is part of the REDCap consortium. In this introduction to REDCap we will discuss:

  • How to request a REDCap project at Boston College
  • How to make sure that your RedCAP project complies with the mandates of your project's IRB approval
  • How to create basic data collection forms
  • An introduction to best practices for setting up your REDCap project
  • Recent improvements in BC’s newest release of REDCap 6.10.1 including offline survey capabilities, text to voice capability, potential for using SMS services (for an additional fee), improved field calculations and more
  • How to enter data into RedCAP
  • How to control RedCAP user access rights
  • How to export your data

Prior to the class, Research Services will create a TEST project for teaching and learning purposes for each class participant.  Research Services staff are also available to meet with members of the Boston College community to discuss individual REDCap projects.

March 1, 2016   12:00 - 1:30 pm O’Neill 246

Introduction to Regression

As the most common methodology in statistical analysis regression is an important tool for any modern researcher.  This course is intended as an introduction to standard or linear regression.  We will focus on estimation methods, identifying and validating model assumptions.  We will also focus on hypothesis testing for regression estimates and statistical model building.  We will use R software but the goal of the course is to learn concepts and is not intended as a tutorial any specific software.  Note:  The mixed modeling course is a natural sequel to Introduction to Regression.

January 26, 2016   12:00 – 1:30  pm  O’Neill 246

Introduction to Qualitative Analysis Using NVIVO 11

This workshop provides an introductory demonstration of how to use NVIVO 11 for qualitative analysis. We will discuss the updates in NVIVO 11 from previous versions. NVIVO 11 can be used to manage large amounts of qualitative data, to code and re-code qualitative data, to keep an audit trail of the analysis process, and to support both individual researchers and research teams in discussing coding and analysis issues. This course is intended for beginning Nvivo users. and intermediate users who have had some exposure the methodologies and theories of qualitative analysis.

This workshop will include a demonstration (non-hands on) format:

  • Qualitative research design
  • Source Preparation
  • NVIVO 11 Project Views (List, Navigation, Detail)
  • Nodes
  • Models
  • Queries
  • Journals
  • Starting a project in NVIVO 11

Additional information on qualitative software and resources at Boston College will be presented.

February 10, 12:00 - 1:30 pm  O'Neill 246

Introduction to Stata 1: Getting Started, Descriptive Stats and do Files

Stata is a powerful, 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 emphasis in this tutorial is on exploring the data, cleaning the data for research purposes, and generating descriptive statistics

  • Loading data
  • Data manipulation
  • Descriptive statisticsDo-files and log files

February 5,  2016 11:30 - 1:00 pm  O'Neill 245

Introduction to Stata 2: Graphing, Dataset Combining, Linear  Regression, Stat/Transfer

Stata is a powerful, 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 emphasis in this tutorial is on basic graphing, merging data, and linear regression.

  • Basic graphing and graph editor
  • Combining multiple datasets
  • Linear Regression in Stata
  • Stat/Transfer, importing and exporting

February 18, 2016 12:00  - 1:30 pm O'Neill 245

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. We will also discuss best practices for curation of both primary and secondary research data. Topics may be customized based on attendees’ Research interests. Please contact for more information.

February 23, 2016 12:00 - 1:30 pm   O’Neill 307

MATLAB 1: Introduction to MATLAB programming

MATLAB fundamentals and the following seminar provide a working introduction to the MATLAB technical computing environment. MATLAB can be used with all aspects of Mathematical computation, analysis, visualization, and algorithm development. This workshop is intended for beginning and intermediate users. No prior knowledge of MATLAB is required. Themes of vector and matrix data analysis, graphical visualization, data modeling, and MATLAB programming are explored by example.

This MATLAB workshop presents:

  • MATLAB Help
  • Interactive Session
  • Editing Script Files
  • Flow Control
  • Scripts and Functions
  • Read and Write Excel and Text Files
  • Toolboxes

January 22, 2016 11:00 - 12:30 pm  O’Neill 245

MATLAB 2: Graphs and Visualization

The MATLAB environment provides a wide variety of techniques to display data graphically. Interactive tools enable you to manipulate graphs to achieve results that reveal the most relevant information about your data. You can also annotate and print graphs for presentations, or export graphs to standard graphics formats. This workshop covers the main MATLAB functions for two- and three-dimensional graphics. We illustrate

  • Two-Dimensional Graphics
  • Basic Plots
  • Axes and Annotation
  • Multiple Plots in a Figure
  • Three-Dimensional Graphics
  • Saving and Printing Figures

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

January 29, 2016 11:00 - 12:30 pm O’Neill 245

Modern Statistics Methods Journal Club:  The Elements of Statistical Learning from Data.

We will continue the Modern Statistics Journal Club in the Winter/Spring Semester 2016.  This group meets approximately once to month to explore new topics in the field of statistics.  With the rapid change and growth in data analytical methods it can be difficult for a data analyst to keep their skills up to date.  The Modern Statistics Journal Club has been created to provide the opportunity for data analysts in the Boston College community a place to explore new methodologies and an opportunity to learn from each other.  
In the fall of 2015 we explored machine learning methods.  This semester we plan to solicit topics from the participants.  We will reserve rooms (one room only this semester) and send out the reading material at least one week before we meet.  We will be meeting on Thursdays at 1 pm once a month.  The dates are February 11, March 17, and April 21.

Primary Data Collection: Best Practices for Researchers

There are methodological considerations for all types of data collection whether quantitative, qualitative or mixed methods data are being used. Our emphasis will be on survey design for quantitative analysis (although the principles discussed will also be applicable to qualitative and mixed methods research and direct data input into an analytical tool). We will discuss how to design online surveys and databases to avoid a lot of pre-analysis data cleaning and data manipulation.  We will also discuss best practices for HIPAA compliance and data security.

March 1, 2016 10:30 am - 12:00 O’Neill 246

SAS Programming I

This tutorial is an Introduction to SAS programming. It is designed for people with a basic knowledge of statistics who are beginners of SAS programming. We will talk about basic steps of SAS programming and structure, and demonstrate the internet resources to get started programming in SAS, including not limited to:

Students are encouraged to bring in their own data problems and SAS programming questions into the tutorial.

  • What is SAS system
  • Introduce SAS work environment
  • Write, submit, debug, and save SAS programs
  • SAS data steps and proc steps
  • Manage SAS libraries and files
  • How to run descriptive statistics
  • How to run basic regressions and other models
  • Internet resources
    • SAS online documents, technical support websites
    • Good SAS learning websites

January 25, 2016 12:00 - 2:00 pm O'Neill 245

SAS Programming II

This tutorial is designed for existing SAS users who have already known the basics of SAS but looking for more advanced tips and skills. We will focus on data manipulations, analytics and data management aspects, including not limited to the following,

Students are encouraged to bring in their own data problems and SAS programming questions into the tutorial.

  • SAS data types, and data type conversions
  • Combine and subset SAS datasets
  •  SAS functions
  • Import/export data from other data sources
  •  SAS SQL procedure and its comparison with DATA step
  •  Program efficiency issues with large datasets
  •  Most widely used statistical procedures
  • Other questions raised by audience

February 1, 2016 12:00 - 2:00 pm O'Neill 245

Statistical Data Conversion

This tutorial is focused on transferring data across different formats.  Research data often come in different formats, such as SPSS, STATA, SAS, Excel, Access, or text files. Researchers often encounter difficulties  converting data from one format to another in order to use their prefered analysis tools.

This tutorial demonstrates how to perform conversions.  We will also discuss how to resolve  problems that might  occur during the process, such as converting variable names. labels, values, data types, missing data, version compatibility, etc. Also we will show how to use StatTransfer  to  transform the data to different formats.

Students are encouraged to bring in their own data problems into the tutorial.  We can  then solve real problems while learning the ropes.

February 4, 2016 12:00 - 1:00 pm O'Neill 245