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Fall 2015 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 (researchservices@bc.edu).  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: capricorn.bc.edu/tutorials.  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 researchservices@bc.edu with the names of the tutorials that you are interested in attending.

Please note that the locations of the tutorials varies.

The Fall 2015 Tutorials are:

Title
Date 
Location
Modern Statistics Methods Journal Club Sep 24 1:00 - 2:00 TBA
Introduction to Regression Sep 9 12:00 - 1:30 O'Neill 245
Introduction to SAS 1 Sep 14 12:00 - 1:00 O'Neill 245
Introduction to SAS 2 Sep 14 1:00 - 2:00 O'Neill 245
Introduction to Multi-Level Modeling Sep 15 12:00- 1:30 O'Neill 246
MATLAB 1: Introduction to MATLAB programming Sep 16 11:00 - 12:30 O'Neill 245
Introduction to BC’s Linux Cluster Sep 16 12:00 - 1:30 O'Neill 246
Introduction to R Sep 22 12:00 - 1:30 O'Neill 245
MATLAB 2: Graphs and Visualization Sep 23 11:00 - 12:30 O'Neill 245
Introduction to GIS Sep 25 10:00 - 11:30 O'Neill 307
Introduction to Stata 1: Getting Started, Descriptive Stats And Do Files Sep 29 12:00 - 1:30 O'Neill 245
Introduction to Stata 2: Graphing, Dataset Combining, Linear Regression, Stat/Transfer Oct 20 12:00 - 1:30 O'Neill 245
Locating And Using Data For Secondary Research At Boston College Oct 6 12:00 - 1:30 O'Neill 307
Creating Web-Based Surveys With Qualtrics Oct 15 1:00 - 2:30 O'Neill 254
Introduction To RedCAP Oct 22 12:00 - 1:30 O'Neill 254
Primary Data Collection: Best Practices For Researchers Oct 15 12:00 - 1:00 O'Neill 254

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 researchservices@bc.edu for a Qualtrics account. Please note the Boston College School with which you are affiliated.

October 15, 2015  1:00 – 2:30 pm  O’Neill 254

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 common commands
  • Compile, debug and run programs
  • How to submit jobs to clusters

Sepember 16, 2015  12:00 - 1:30 pm O'Neill 246

Introduction to GIS

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.

September 25, 2015 10:00 - 11:30 pm O’Neill 307

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
  • How to enter data into RedCAP
  • How to control RedCAP user access rights
  • How to create ad hoc reports and 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.

October 22, 2015 12:00 - 1:30 pm  O’Neill 254

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.

September 15, 2015 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.
September 22, 2015 12:00- 1:30 pm O’Neill 245.

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.

September 9, 2015   12:00 – 1:30  pm  O’Neill 245

Introduction to SAS I

This tutorial is an Introduction to SAS.  It is designed for people with a basic knowledge of statistics who have never used SAS.  We will talk about the basics including:

  • What is SAS system
  • Introduce SAS work environment
  • Write, submit, debug, and save SAS programs
  • Input data into SAS, exchange data from other data formats
  • How to run descriptive statistics
  • How to run basic regressions and other models

September 14, 2015 12:00 - 1:00 pm O'Neill 245

Introduction to SAS II

This tutorial builds on SAS I. We will focus on analytics and data management aspects, introduce basic steps of SAS programming and structure, and demonstrate the internet resources to get started programming in SAS

Data manipulations:

  • SAS data types, and data type conversions
  • Combine and subset SAS datasets
  • SAS functions
  • SAS data steps and proc steps
  • Manage SAS libraries and files

Internet resources:

  • SAS online documents, technical support websites
  • Good SAS learning websites

September 14, 2015 1:00 - 2:00 pm O'Neill 245

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 statistics
  • Do-files and log files

September 29, 2015 12:00 - 1:30 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

October 20, 2015  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 datasupport@bc.edu for more information.

October 6, 2015 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

September 16, 2015 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.

September 23, 2015 11:00 - 12:30 pm  O’Neill 245

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

As the ability to collect, store, and process data has grown with the digital revolution, the field of statistics has had its own revolution to keep up with the new demand.  Although classical methods which have the focus of a statistical education through the early 2000’s remain at the center of statistical inference, they are no longer sufficient for many modern data analysis applications.   Outside of traditional inference with known group structures many modern analysis are focused on finding unknown structures with large datasets.   These applications have many names, originally called data mining, but they are now more generally referred to as statistical learning methods. 

Given the ubiquity of these types of problems and the success data analysts have had using these methods it is important for the modern statistician to keep current with these methodologies.  The goal of this journal club is to provide a place for modern researchers and data users to help each other keep current with new methodologies and learn from each other’s expertise and intuitions. For the fall semester we will meet Thursdays at 1:00 pm one time per month for one to two hours depending upon interest.  To get things started during this semester we will read chapters from "The Elements of Statistical Learning" by Hastie, Tibshirani and Friedman.  This book is available as an e-book from the Boston College Library so all participants will have free access.  Research Services will provide a monthly reading list, meeting rooms, and reminders. 

Tentative meeting dates are September 24, October 22, November 19 and December 10 from 1:00 - 2:00.  If interested, please sign up, we will add you to an email list.

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.


October 15, 2015 12:00  - 1:00 pm  O’Neill 254