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Spring 2014 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 Spring 2014 Tutorials are:

Title
Date 
Location
Introduction to Regression Jan 21 12:00 - 1:30 Carney 33
MATLAB 1:Introduction Jan 27 2:00 - 3:30 O'Neil 245
Introduction to the Linux Clusters Jan 29 12:00 - 1:30 O'Neil 245
MATLAB 2: Matrices Jan 31 11:00 - 12:30 O'Neil 245
Introduction to R Feb 4 1:30 - 3:00 O'Neil 245
MATLAB 3: Graphs and Visualization Feb 3 11:00 - 12:30 O'Neil 245
MATLAB 4: Introduction to Statistics Feb 5 11:00 - 12:30 O'Neil 245
Creating Web-based Surveys with Qualtrics Feb 5 12:00 - 1:30 Carney 33
Introduction to GaussView and Gaussian Feb 19 12:00 - 1:30 O'Neil 245
Introduction to Moderating Variables/interactions Feb 19 12:00 - 2:00 Carney 33
Taking Care of Your Data for the Social Sciences Feb 27 1:00- 2:15 O'Neill 307
Taking Care of Your Data for the Sciences Feb 27 4:00 - 5:15 O'Neill 307
Introduction to Mixed Modeling Mar 11 12:00 - 1:30 Carney 33
Introduction to Atlas.ti 7 Mar 12 12:00 - 1:30 Carney 33
Microsoft Access Mar 13 10:30 - 11:30 O'Neill 307
Locating and Using Data for Secondary Research Mar 13 12:00 - 1:30 O'Neill 307
Data Extraction and Transformations Mar 20 12:00- 1:30 Carney 33
Stata 1: Descriptive Analysis Apr 10 12 :00- 1:30 Carney 33
Stata 2: Regression Analysis Apr 11 12:00- 1:30 Carney 33
Stata 3: Panel Data Analysis Using Stata Apr 17 12 :00- 1:30 Carney 33

Creating Web-based Surveys with Qualtrics

Qualtrics offers a way 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. Qualtrics also offers foreign language functionality. Working within pre-defined templates, you can use many different types of questions, including text, multiple checkboxes, sliders, single-answer radio buttons, Likert scales.  Qualtrics also offers extensive branching functionality. Once the survey is completed, data can be downloaded into a format that can be used with Excel, Stata, SPSS, Nvivo, HyperResearch or Atlas.ti or other quantitative and qualitative analysis programs.

This tutorial will also include a section on research protections and informed consent with respect to online survey development, distribution, and analysis. BC’s School of Arts & Sciences, CSON, CSOM, LSOE, and GSSW have purchased annual Qualtrics licenses that are available for use by faculty, staff, and students in those schools.  People not in these schools are also welcome to attend this tutorial.  BC community members not in those schools may register for a limited free Qualtrics account at qualtrics.com. They may also obtain free access to Qualtrics online tutorials and help articles. It is recommended that you contact your school (A&S (researchservices@bc.edu), CSON (maria.vitone@bc.edu), CSOM, (linda.salisbury@bc.edu), GSSW (rita.vatcher.1@bc.edu), or LSOE (amy.ryan.2@bc.edu) to obtain a Qualtrics account prior to the tutorial.

Customized Qualtrics training at all levels is available for classes as well as individual researchers by contacting researchservices@bc.edu.

February 5, 2014  12:00 - 1:30 pm Carney 33

Data Extraction and Transformations: Preparing Your Data for Analysis

Research Services receives many questions about working with secondary data files from various data  collections and repositories as well as about working  with primary data files that have been exported from survey tools such as Qualtrics or Survey Monkey.

This tutorial will review some "tricks of the trade" for working with your files and preparing your data for analysis in the quantitative analysis tool of your choice (R, Stata, SAS, SPSS, etc.)

Topics include:

  • CSV files
  • Extracting data from web pages
  • Extracting data from PDF files
  • Using Stat Transfer
  • Combining data in Stata
  • Appending
  • Matching/Merging

March 20, 2014    12 :00- 1:30 pm  Carney 33

Introduction  to Atlas.ti 7

This tutorial will include an overview of various computer assisted qualitative data analysis tools (CAQDAS) available for qualitative and mixed methods research.
Atlas.ti is a software package for the analysis of qualitative data particularly on large projects that require collaboration between multiple sites and multiple coders.

Topics will include:

  • Demonstrate the V7 Interface
  • Demonstrate tools for the management of qualitative analysis projects in V7
  • Demonstrate the functionality in the Atlas.ti managers (primary document, memo, and code managers)
  • Demonstrate importing surveys into Atlas.ti

Customized Atlas.ti training (as well as training on HyperResearch, Dedoose, and Nvivo at all levels) is available for classes as well as individual researchers by contacting researchservices@bc.edu.

March 12, 2014 12:00 - 1:30 pm Carney 33

Introduction to GaussView & Gaussian

GaussView is a graphical use interface (GUI) designed to be used with Gaussian to make calculation preparation and output analysis easier, quicker and more efficient. Gaussian is one of the most popular and widely used electronic structure programs and powerful computational chemistry package. It can predict properties of molecules and reaction. This tutorial will cover:

  • Overview of computational chemistry application in BC
  •  Basic Linux Cluster knowledge
  • History of Gaussian and Gaussian View
  • Gaussian View and Gaussian Capabilities
  • How to access and use Gaussian View at BC clusters
  • Input file preparation and keyword specification for Gaussian
  • Running Gaussian 09 at cluster

February 19, 2014 12:00 - 1:30 pm O'Neil 245

Introduction to the 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 two clusters (Scorpio and Pleiades) available. This hands-on tutorial covers the following topics:
 
Overview of two 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

January 29, 2014 12:00 - 1:30 pm O'Neil 245

Introduction to Mixed 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.

March 11,  2014 12:00 - 1:30 pm  Carney 33

Introduction to Moderating Variables/Interactions

Researchers in the social sciences are often interested whether the relationship between two variables might vary for different groups or within different settings. Moderating variables allow researchers to model these types of relationships. This tutorial will provide an introduction to moderating variables. It will describe how to create moderating variables, how to correctly analyze them within a regression model, and how to interpret moderation effects. Demonstrations will be conducted in both SPSS and in Stata.

February 19, 2014 12:00 - 2:00 pm Carney  33

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 4,  2014 1:30 - 3:00 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.

January 21, 2014 12:00 - 1:30  pm Carney 33

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
  • How to download the data onto your desktop, including how to import into quantitative analytical tools such as Stata or SPSS.  
  • Qualitative secondary data will also be discussed
  • 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. Please contact datasupport@bc.edu for more information.

Please see the Transforming Data workshop on March 20 for a follow-up on how to prepare your data for analysis once you have found it.

March 13, 2014, 12:00 - 1:30 pm O’Neill 307

MATLAB 1: Introduction

MATLAB fundamentals and the following seminars 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 will present:

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

January 27, 2014    2:00 - 3:30 pm O’Neill 245

MATLAB 2: Matrices and Data Analysis

Matrices are fundamental to MATLAB, and familiarity with matrix generation and manipulation is important in many applications. The most basic MATLAB data structure is the matrix: a two-dimensional, rectangular shaped data structure capable of storing multiple elements of data in an easily accessible format. The operations in MATLAB are designed to be as natural as possible and MATLAB allows you to work with entire matrices quickly and easily. This workshop will discuss:

  • Matrix Generation
  • Subscripting and the Colon Notation
  • Matrix and Array Operations
  • Matrix Manipulation
  • Data Analysis

January 31, 2014    11:00 - 12:30  O’Neill 245

MATLAB 3: 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. In this workshop we cover 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.

February 3, 2014    11:00 - 12:30  O’Neill 245

MATLAB 4: Introduction to Statistics 

This MATLAB hands-on practice workshop with focus on Statistical Toolbox and illustrate some of the methods used in Applied Statistics. The objective is to work with data in the MATLAB environment, perform statistical analysis, and visualize data in a variety of ways. It is assumed that participants have already some knowledge of MATLAB (at the level of previous three workshops) and some background in Applied Statistics. We will illustrate:

  • Descriptive statistics
  • Statistical Visualization
  • Regression analysis

February 5, 2014    11:00 - 12:30 pm O’Neill 245

Microsoft Access

Microsoft Access 2010 is an information management tool that helps you store information, analyze data, and create reports. 

Access 2010 is combined with Microsoft Office 2010.  This tutorial will introduce the fundamental of the Access, includes creating database, tables, fields, reports, and how to enter and save data. This tutorial will help you get started with it. 



March 13, 2014, 10:30 - 11:30am O'Neill 307.

Stata 1: Descriptive Analysis

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, using graphs, employing descriptive statistics and running simple regressions.

The following topics will be covered:

  • Getting started: open data files, use variable manager.
  • Exploring the data: check variables, use labels and filters, describe data.
  • Modifying the data: create new variables, recode data, examine and impute missing values.
  • Working with datasets: append and merge datasets.
  • Producing output: log-files, label book, codebook, graphs, and simple regressions.

April 10, 2014    12 :00- 1:30 pm  Carney 33

Stata 2: Regression Analysis

This hands-on tutorial is designed for novice users who are familiar with the basics of Stata. The emphasis in this tutorial is on linear regressions and the basics of analysis with discrete data, where categorical variables are regressors or the dependent variable. Basic programming concepts are introduced. A basic knowledge of the software Stata is required; those who are new to Stata are strongly encouraged to attend the Stata 1 tutorial first.

The following topics will be covered:

  • Linear regression: OLS, significance tests, post-estimation analysis.
  • Categorical variables: factor variables, interactions and interpretation.
  • Categorical outcomes: logit and probit models, multinomial and ordered logit, interpretation.
  • Programming skills: creating and using do-files; documenting work to ensure reproducibility.

April 11, 2014 12:00 - 1:30 pm   Carney 33

Stata 3: Panel Data Analysis Using Stata

This hands-on tutorial is designed as an introduction for beginning users who have a basic understanding of the Stata environment and some statistical experience with conducting regression analysis. This tutorial will introduce some of the techniques developed for use with longitudinal data and repeated measurements. A basic knowledge of the software Stata is required; those who are new to Stata are strongly encouraged to attend the Stata 1 tutorial first.

The following topics will be covered:

  • Pooling Regression
  • Omitted Variable Bias
  • First-Difference Model
  • Fixed Effects
  • Random Effects

April 17, 2014 12:00 - 1:30 pm   Carney 33

Taking Care of Your Data – for You and for Others – for the Social  Sciences


The Libraries and Research Services will provide a critical overview of “best practices” for research data management, including development of “data management plans”.  Funders (government agencies, in particular) and journal publishers are increasingly requiring submission of dthese plans incorporating all of these practices, along with placing greater emphasis on sharing and long-term preservation of research data.   You’ll learn how to safe-guard your data through recommended practices for naming, file format choice, file organization, storage, backup and documentation, as well as information about valuable university data analysis and support services. You’ll learn about options for long-term archiving of your data and data sharing, including discovery of quality social sciences data repositories and creation of metadata to enhance discovery of that data.  You’ll also learn how to cite your data/data sets, further enhancing the discoverability and impact of your work.

February 27, 2014 
1:00 – 2:15 pm O’Neill 307

Taking Care of Your Data – for You and for Others – for the Sciences

The Libraries and Research Services will provide a critical overview of “best practices” for research data management, including development of “data management plans”.  Funders (government agencies, in particular) and journal publishers are increasingly requiring submission of these plans incorporating all of these practices, along with placing greater emphasis on sharing and long-term preservation of research data.   You’ll learn how to safe-guard your data through recommended practices for naming, file format choice, file organization, storage, backup and documentation, as well as information about valuable university data analysis and support services. You’ll learn about options for long-term archiving of your data and data sharing, including discovery of quality data repositories in the various scientific disciplines and creation of metadata to enhance discovery of that data.  You’ll also learn how to cite your data/data sets, further enhancing the discoverability and impact of your work.

Thursday, February 27, 2014 
4:00 – 5:15 pm O’Neill 307