Download here - Faculty of Graduate Studies : Athabasca University

Athabasca University Faculty of Graduate Studies’ Workshop
Statistics Software Tools
Saturday, May 6, 2017, 9:00 am - 4:30 pm
Available for All Graduate Students of
Athabasca University, University of Lethbridge, University of Alberta,
and University of Calgary
Attendance may be online via Adobe Connect or In-person at
Room 1112, AU Edmonton, Peace Hills Trust Tower, 12th Floor, 10011 109 Street,
Edmonton, AB T5J 3S8
Google Map | Website
(Registration deadline is May 1, 2017)
Agenda
Moderator: Dr Oscar Lin, Associate Dean of Faculty of Graduate Studies, Athabasca University
Session 1
9:00 am – 11:00 am
Introduction to SPSS
Professor: Dr. Shawn Fraser, Faculty of Health Disciplines, Athabasca University
You will learn to:
 Create and format a datafile
 Enter data
 Import and export datafiles
 Score subscales/scales, code and transform variables
 Generate descriptive statistics and explore data
 Run basic statistics, tables and figures
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Add extensions to SPSS
View and use syntax
11:00 am – 11:15 am
Break
Pre-requisite: This session is mainly designed for the students who have completed an
undergraduate statistics course. No software programming background is needed.
Session 2
11:15 am – 12:15 pm
Introduction to R for Data Analysis
Professor: Dr. Dunwei Wen, Faculty of Science and Technology, Athabasca University
You will learn to:
 Explain data objects and manipulations of R programming language
 Load and explore data in R Commander (Rcmdr)
 Use Rcmdr to run and present basic descriptive analysis
 Explore, code and perform R programs in RStudio
 Use R graphics for data visualization
 Perform basic statistical inference including estimation and hypothesis test
 Perform analysis of variance
 Perform basic predictive analysis including linear regression, multiple regression and
logistic regression
Pre-requisite: This session is mainly designed for students from all fields who have completed
an undergraduate statistics course and have basic computer programming knowledge.
12:15 pm – 1:15 pm Lunch (Provided by Athabasca University)
1:15 pm – 2:15 pm
Introduction to R for Data Analysis (continued)
Professor: Dr. Dunwei Wen, Faculty of Science and Technology, Athabasca University
2:15 pm – 2:30 pm Break
Session 3
2:30 pm – 4:30 pm
Professor:
Introduction to MATLAB
Dr. Ali Dewan, Faculty of Science and Technology, Athabasca University
You will learn to:
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Create scripts and functions in Matlab environment
Manipulate matrices and arrays
Use Matlab built-in functions for data visualization
Use dataset, datafiles, and mapping functions in PRTools
Train and test different classifiers, such as k-NN, SVM, and Neural Networks
Use sequential, parallel and stacked combinations of classifiers
Evaluate performance of classifier systems - cross validation, learning curves, and
ROC
Pre-requisite: This session is mainly designed for the students who have completed an
undergraduate statistics course. Some experience in basic computer programming is
also preferable. Students from a Science and Engineering background will benefit from this
session. Students from other backgrounds will also benefit by learning how to analyze and
visualize data using Matlab tools.
Short bios of Professors:
Dr. Shawn Fraser:
Dr. Fraser is an Associate Professor in the Faculty of Health Disciplines at
Athabasca University. He is also an Adjunct Assistant Professor, Physical
Education and Recreation, University of Alberta. Dr. Fraser was acting Dean
of the Faculty of Graduate Studies at Athabasca University during 20132014. He is Member of the Board of Scientific and Policy Advisors for the
American Council on Science and Health. Research Advisor Committee,
Alberta Centre for Active Living Research Affiliate, Glenrose Rehabilitation
Hospital.
He has been delivering SPSS workshops for the Faculty of Graduate Studies since 2011, with a
goal of making statistics accessible.
Dr. Fraser’s research interests include understanding how stress can impact upon rehabilitation
success for heart patients. For example, the period following a heart attack or diagnosis of heart
disease can be stressful. This stress might impact upon adherence to exercise or even the success
of rehabilitation. Current activities include examining cardiovascular responses to mental stress
in heart patients. In the future, how mental stress can influence cardiovascular responses to
physical activity will be examined.
Dr. Dunwei Wen:
Dr. Dunwei Wen is Associate Professor in the School of Computing and
Information Systems at Athabasca University, Alberta, Canada. He
received his PhD in pattern recognition and intelligent systems from
Central South University, and a MSc and BEng from Tianjin University
and Hunan University respectively. Prior to his current position, he was a
visiting scholar in the Department of Computing Science at the
University of Alberta, and Professor at the School of Information Science
and Engineering at Central South University.
Dr. Wen’s research interests include artificial intelligence, machine learning, natural language
processing, data mining, text analytics, pattern recognition and intelligent systems, and their
application in industry, medicine and education. He has published more than sixty papers in peerreviewed journals and conferences. Dr. Wen has taught a number of graduate and undergraduate
courses in computing and information systems such as Artificial Intelligence, Statistical Language
Processing for Text Analytics, Business Intelligence, Theory of Computation, Data Mining,
Intelligent Control, and Foundations of Software Techniques, and has supervised fifty graduate
students and research assistants in these universities.
Dr. Ali Dewan:
Dr. Ali Dewan is an Assistant Professor at the School of Computing and
Information Systems, Athabasca University (AU), Canada. He received his
PhD in Computer Engineering from Kyung Hee University (KHU), South
Korea. From 2003 to 2009, he was a Faculty Member at Chittagong
University of Engineering and Technology, Bangladesh. From 2009 to
2014, he was a Postdoctoral Fellow at Concordia University and École de
Technologie Supérieure, Montreal, Canada.
Dr. Dewan’s research interests include image processing, computer vision,
motion detection, tracking, machine learning, pattern recognition, artificial
intelligence and medical image analysis. He has published more than thirty papers in peer reviewed
journals and conferences, and has actively taken part in several scholarly and applied research projects
supported by NSERC, MDEIE, and ReSMiQ, Canada. Dr. Dewan is a Member of the Institute of
Electrical and Electronics Engineers (IEEE) and Canadian Artificial Intelligence Association (CAIAC).
He serves as a program committee member for several international conferences such as ICALT,
Canadian AI, ICIEV, ICCIT, and ISCAS and as a reviewer for several journals including ACM
Computing Survey, IEEE TIP, IEEE TMI, IEEE TITB, and Neural Computing and Applications. He
is serving as an Associate Editor for the Circuits Systems and Signal Processing (CSSP) and the
Computer journals.
Notes:
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The focus of the session should be practical (learning by doing principle) to enhance the
learning relevance to workshop participants.
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Participants will be sent course packages including lecture notes, references, and
instructions on how to download and install the research software tools (e.g. free trial
versions) prior to the workshop session.
Students who attend the workshop in person should bring their own laptops (Wi-Fi will
be available),
Given the introductory level, the workshop learning outcomes are as follows:
1) Describe diverse quantitative research software tools;
2) Discuss the relevance of various research software tools for data analyses;
3) Apply some basic operations/functionalities with diverse quantitative research
software tools;
4) Assess the overall usefulness of diverse quantitative research software tools.