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Research Services

Spring 2010 Tutorials

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

Creating Web-based Surveys with Survey Monkey

Survey Monkey offers a way to create surveys without complicated programming or coding. Working within pre-defined templates, you can use several different types of questions, including text, multiple checkboxes, single-answer radio buttons, Likert scales and free text responses. Once the survey is completed, data can be downloaded into a format that can be used with Excel, SPSS, or other analysis programs. The tutorial will cover:

  • Getting started with Survey Monkey
  • Creating and editing surveys 
  • Publishing the survey on the web
  • Closing the survey and downloading data
  • Important survey design considerations

In addition to Survey Monkey, we will also briefly discuss other online survey  providers, php/ESP, and custom design services. Principles taught in this class will also apply to Qualtrics, Zoomerang, and other online survey design tools.

March 10, 2010, 12:00 - 1:30 O'Neill 245

Introduction to ArcGIS

Geographic Information Systems (GIS) are used today to analyze and represent data with geographical reference on maps. Such applications are widely used in academia, private industry and government agencies. ArcGIS Desktop software 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 various GIS tasks, from simple to advanced, including:  mapping, geographic analysis,  geostatistics, data editing, compilation, management and visualization. ArcGIS Desktop is scalable to meet the needs of many types of users.

This session will introduce users to:

  • ArcGIS software, data and technical support at Boston College
  • License options
  •  Main ArcGIS features and capabilities (ArcMap, ArcCatalog, ArcTool, ArcGlobe)
  •  Demos using Census data and Environmental data. Options to get data and training will be also discussed.

No prior knowledge of ArcGIS is required.

January 29, 2010, 3:30 - 5:00 pm   O'Neill 245

Introduction to Lisrel: Confirmatory Factor Analysis and Path Models

This tutorial will explore the basic steps in understanding the terminology for confirmatory factor analysis and path models for use in the social sciences. Confirmatory Factor Analysis (CFA) emphasized the use of theory in hypothesis testing, and can be used in conjunction with path models for causal modeling. Structured Equation Modeling in the social sciences combines factor analysis and path models to account for measurement error in estimating parameters. The goal of this session is to introduce some of these concepts when using Lisrel.

April 14, 2010 12:00 1:00 pm O'Neill 245

Introduction to Qualitative and Mixed Methods Research using Computer Assisted Qualitative Data Analysis Tools

This workshop provides an introductory discussion and demonstration of how to prepare a qualitative or mixed methods analysis project for use with computer assisted qualitative analysis tools such as Nvivo, HyperResearch, or Atlas.ti. These tools 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 workshop will be given in a demonstration (non-hands on) format. Nvivo will be used for demonstration purposes. Follow up consultations are available with individual research teams. We will include a discussion of the strengths and weaknesses of the various tools.

March 24, 2010 12:00 - 1:30 pm  O'Neill 245

Introduction to SPSS

SPSS is a powerful and yet easy to use integrated collection of quantitative analysis software that is particularly popular with social science researchers. This hands-on tutorial is designed as an introduction for beginning users who are just getting started using SPSS. No prior knowledge of SPSS is required. The following topics will be covered:

  • Overview of SPSS, including how SPSS compares to the other most popular statistical packages and special features of SPSS.
  • Getting started with SPSS
  • Working with data in SPSS
  • SPSS graphs
  • The last part of this tutorial will be devoted to an overview of other statistical methods using SPSS including correlation and regression.

March 17, 2010 12:00 - 1:30 pm O'Neill 245 

Getting Started with HLM6

This tutorial will explore the basic concepts involved in applying hierarchical linear modeling using HLM6. Particular focus will be placed on understanding how heteroskedastic errors may occur when using ordinary least squares for analysis, and how the method of mixed modeling may be able to account for this problem in the social sciences using HLM6. We will cover the creation of a multivariate data matrix (mdm) file using the software, and proceed to generating results for a null model along with calculating the Intraclass Correlation Coefficient.

April 7, 2010 12:00-1:00 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. Topics may be customized based on attendees’ research interests. Please contact datasupport@bc.edu for more information.

Feb 4,  2010 12:00 - 1:30 pm   O’Neill 307

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) would 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 workshop will present:

  • Matlab documentation and help
  • Starting and quitting Matlab
  • How to use Matlab on BC's Linux cluster
  • Interaction and Script Files
  • Automatic Storage Allocation
  • Functions with Variable Arguments Lists
  • Mathematical Functions
  • Relational and Logical Operators
  • Flow Control
  • Importing and exporting text and Excel data

Note: Sign up for only one session.  The content is identical.
Session 1 February 1, 2010,10:00 am - 11:30 am O'Neill 245
Session 2 February 1, 2010  3:30 - 5:00 pm    O'Neill 245 

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. 

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

  • Two-Dimensional Graphics
  • Basic Plots
  • Axes and Annotation
  • Multiple Plots in a Figure
  • Three-Dimensional Graphics
  • Specialized Graphs for Displaying Data
  • Saving and Printing Figures

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

Note: Sign up for only one session.  The content is identical.
Session 1: February 8, 2010  10:00 am - 11:30 am O'Neill 245  
Session 2: February 8, 2010 3:30 - 5:00 pm   O'Neill 245

MATLAB 3: Statistics

This MATLAB hands-on practice workshop, with focus on statistical toolbox, will illustrate some of the methods used in univariate, and bivariate statistics. The objective is to learn to work with data in the MATLAB environment, perform statistical analysis, and visualize data in a variety of ways. It is assumed that participants already have 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
  • Random variables, Sampling distributions, Bootstrapping
  • Explore regression analysis for bivariate data
  • Correlation and covariance

Note: Sign up for only one session.  The content is identical.
Session 1: February 15, 2010 10:00 am - 11:30 am  O'Neill 245
Session 2: February 15, 2010  3:30 - 5:00 pm   O'Neill 245

MATLAB 4: Multivariate statistics

High-dimensional data present many challenges for statistical visualization, analysis, and modeling. Data visualization is impossible or difficult beyond a few dimensions. Thus, pattern recognition, data preprocessing, and model selection must rely heavily on numerical methods. Often, many of the dimensions in a data set may be irrelevant or redundant. Because of these challenges, multivariate statistical methods often begin with some type of dimension reduction, in which data are approximated by points in a lower-dimensional space.

Principal component analysis (PCA) and Factor analysis (FA) aim at reducing the dimensionality of a complex set of data. These two techniques are closely related but have some important differences. PCA is a mathematical approach whose objective is to maximize variance and summarize data in fewer dimensions, for example, to visualize it. FA is a statistical method that analyses the correlation structure of the data and it is often used to build explanatory models of data correlations.

This workshop will provide an introduction to PCA and FA, illustrating some practical examples. It is assumed that participants have already some knowledge of MATLAB and Applied Statistics.

Note: Sign up for only one session.  The content is identical.
Session 1: February 22, 2010 10:00 am - 11:30 am O'Neill 245
Session 2: February 22, 2010 3:30 - 5:00 pm  O'Neill 245 

MATLAB 5: Numerical Methods, Part 1

This MATLAB workshop will deal with integrals evaluation and with the numerical solution of ordinary differential equations (ODE).  Such equations arise in many different contexts including mathematics, physics, chemical kinetics, geophysics, mechanics, astronomy and population modeling.  Much study has been devoted to the solution of ordinary differential equations. In the case where the equation is linear, it can be solved by analytical methods. Most of the interesting differential equations are non-linear and, with a few exceptions, cannot be solved exactly. Approximate solutions are possible using numerical methods.

The topics that will be covered are:

  • Quadrature
  • Ordinary Differential Equations (ODE)
  • Stiff ODE.

It is assumed that participants already have some knowledge of MATLAB and background in integral calculus and dynamic systems.

Note: Sign up for only one session.  The content is identical.
Session 1: March 8, 2010   10:00 - 11:30 am O'Neill 245
Session 2: March 8, 2010   3:30 - 5:00 pm    O'Neill 245

MATLAB 6: Numerical Methods, Part 2

This MATLAB workshop will deal with functions that allow for the solution of problems involving polynomials, nonlinear equations, and optimization.
It is assumed that participants already have some knowledge of MATLAB (having a grasp on how to deal with MATLAB functions would be beneficial), background in statistics (Data fitting) and optimization theory.

The topics that will be covered are:

  • Polynomials (Evaluation, Root finding and Data fitting)
  • Nonlinear equations
  • Optimization.

Note: Sign up for only one session.  The content is identical.
Session 1: March 15, 2010   10:00 - 11:30 am O'Neill 245
Session 2: March 15, 2010    3:30 - 5:00 pm  O'Neill 245

Matlab 7: Time series analysis: Part 1

In statistics, signal processing, geophysics, econometrics, and financial mathematics, a time series is a sequence of data points, measured typically at successive times spaced at uniform time intervals. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Methods for time series analyses may be divided into two classes: time-domain methods and frequency-domain methods. This workshop will focus on the former.
The basic concepts that will be covered are:

  • Stationarity
  • Linear trends
  • Seasonality
  • Autocorrelation
  • ARMA modeling
  • GARCH modeling

It is assumed that participants already have some knowledge of MATLAB at the level of the first two workshops.

Note: Sign up for only one session.  The content is identical.
Session 1: March 22, 2010 10:00 - 11:30 am O'Neill 245
Session 2: March 22, 2010 3:30 - 5:00 pm    O'Neill 245

Matlab 8: Time series analysis: Part 2

This workshop will focus on the frequency domain analysis of a time series.
A time-domain graph shows how a signal changes over time, whereas a frequency-domain graph shows how much of the signal lies within each given frequency band over a range of frequencies.  Such approach is valuable in time series analysis in a wide range of applications, from physics, geophysics, econometrics and finance. We will investigate Matlab functions from the Signal Processing toolbox and from Wavelet toolbox.

The basic concepts that will be covered are:

  • Discrete Fourier transform
  • Fast Fourier transform
  • Filtering
  • Periodogram
  • Spectrum

It is assumed that participants already have some knowledge of MATLAB at the level of the first two workshops.

Note: Sign up for only one session.  The content is identical.
Session 1: March 29, 2010 10:00 - 11:30 am O'Neill 245
Session 2: March 29, 2010 3:30  - 5:00 pm  O'Neill 245

SAS 1: Introduction to SAS

Statistical Analysis Software (SAS) is a powerful software which is widely used in statistical analysis.  This hands-on tutorial is an introduction for beginning users. No prior experience with SAS software is needed. The following topics will be covered:

  • Getting started with SAS
  • Temporary versus Permanent SAS data sets
  • Using SAS procedures
  • SAS data sets versus raw data, SPSS, and PC database files.
  • SAS Analyst

January 27, 2010 12:00-1:15 pm  O'Neill 245

SAS 2: Introduction to SAS, Part 2

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

  • Modifying a data set using the SET statement
  • IF-THEN/ELSE statements
  • Stacking data sets by using the SET statement
  • Combining data sets using a one-to-one match merge
  • Combining data sets using a one-to many match merge
  • Using basic statistical procedures: PROC UNIVARIATE, PROC MEANS, PROC FREQ, PROC REG;

February 3, 2010 12:00-1:15pm O'Neill 245

Stata 1: Learning Stata

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:

  • Getting started with Stata
  • Creating and using "log" files
  • Descriptive statistics
  • Creating variables
  • Labeling variables and values
  • And some other introductory commands.

February 10, 2010  12:00 - 1:00 pm  O'Neill 245

Stata 2: Linear Regression

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

  • Simple regression models
  • Significance tests for coefficients
  • Using indicator variables in a linear regression model
  • Using and interpreting interactions between regressors
  • Creating and using "do" files
  • Using Stata new factor variables and the new margins command 

February 17, 2010 12:00 - 1:00 pm  O'Neill 245 

Stata 3: Discrete Choice Models

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

  • Logistic regression analysis (and a little bit of probit)
  • Odds ratio
  • Marginal effects and Elasticities

February 24, 2010  12:00 - 1:00 pm  O'Neill 245