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 on-line 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

Moderator: Dr. Oscar Lin, Associate Dean, Faculty of Graduate Studies, Athabasca University

Agenda

Session 1

9:00 am – 11:00 am Introduction to SPSS

Professor: Dr. Shawn Fraser, Faculty of Health Disciplines, Athabasca University

From this part of the workshop, you will learn to:o Create and format a datafileo Enter data o Import and export datafileso Score subscales/scales, and code transform variableso Generate descriptive statistics and explore datao Run basic statistics, tables and figureso Add extensions to SPSSo View and use syntax

15-minute Coffee Break

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

From this part of the workshop, you will learn to:o Explain data objects and manipulations of R programming languageo Load and explore data in R Commander (Rcmdr) o Use Rcmdr to run and present basic descriptive analysiso Explore, code and perform R programs in RStudio o Use R graphics for data visualizationo Perform basic statistical inference including estimation and hypothesis testo Perform analysis of varianceo Perform basic predictive analysis including linear regression, multiple regression and logistic regression

12:15 pm – 1:15 pm Lunch

1:15 pm – 2:15 pm Introduction to R for Data Analysis (continued)

Professor: Dr. Dunwei Wen, Faculty of Science and Technology, Athabasca University

15-minute Coffee Break

Session 3

2:30 pm – 4:30 pm Introduction to MATLAB

Professor: Dr. Ali Dewan, Faculty of Science and Technology, Athabasca University

MATLAB (MATrix LABoratory) is a popular mathematical software package, that is used extensively in both academia and industry. It provides interactive programming capabilities for numerical computation and data visualization, which is very useful for almost all areas of science and engineering.

MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, C#, Java, Fortran and Python.

PRTools (Pattern Recognition Tools) is a MATLAB toolbox for pattern recognition which is freely available online. PRTools supplies more than 300 user routines for traditional statistical pattern recognition tasks. It includes procedures for data generation, training classifiers, combining classifiers, features selection, linear and non-linear feature extraction, density estimation, cluster analysis, evaluation and visualization.

The purpose of this workshop is to familiarize the beginners to MATLAB and PRTools, by introducing the basic features and commands of the tool. The presentation will also include some problem-based demos of MATLAB and PRTools to make the participants learning easy and effective.

After completing this workshop, the participants will be able to do some basic programming in MATLAB and use some functionalities of PRTools. The participants will be able to extend their knowledge further by going through some references that will be provided at the end of the presentation. Participants having a little knowledge of computer programming and pattern recognition will be more benefitted from this presentation.

Short bios of Professors:

Dr. Shawn Fraser:

Dr Fraser is an Associate Professor of Faculty of Health Disciplines of Athabasca University. He is also an Adjunct Assistant Professor, Physical Education and Recreation, University of Alberta. Dr Fraser was acting Dean of Faculty of Graduate Studies of Athabasca University during 2013-2014. 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 Grad 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 for people. 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, I will examine how mental stress can influence cardiovascular responses to physical activity.

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 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 peer-reviewed 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 Dewa is an Assistant Professor in the School of Computing and Information Systems at Athabasca University (AU), Alberta, Canada. Dr. Dewan received his PhD in Image Processing and Computer Vision from Kyung Hee University (KHU), South Korea, in 2009. He received his BSc in Computer Science and Engineering from Khulna University, Bangladesh, in 2003. From 2003 to 2009, he was a Faculty Member in the Department of Computer Science and Engineering, Chittagong University of Engineering and Technology, Bangladesh. From 2009 to 2012, he was a Postdoctoral Fellow at Concordia University, Montreal, Canada. From 2012 to 2014, he was a Postdoctoral Fellow at École de Technologie Supérieure, Université du Québec, Canada.

Dr. Dewan’s research interests include image processing, computer vision, machine learning, biometric recognition, motion detection, tracking, medical image analysis, artificial intelligence, and multimedia technology. Dr. Dewan’s current research aims at adaptive appearance modeling of faces to improve face recognition and tracking in video surveillance, facial expression recognition for students’ affective state analysis in online education, and resource allocation and scheduling of tasks to achieve operational efficiency in oil and gas industry. Dr. Dewan has published more than thirty journal and conference peer-reviewed papers, and has actively taken part in several scholarly or applied research projects from national grant sources including NSERC, MDEIE, and ReSMiQ, Canada.Dr. Dewan is a Member of Institute of Electrical and Electronics Engineers (IEEE) and Canadian Artificial Intelligence Association (CAIAC). He serves as program committee member of several international conferences such as ICALT, Canadian AI, ICIEV, ICCIT, and ISCAS and as reviewer for many journals including ACM Computing Survey, IEEE TIP, IEEE TMI, IEEE TITB, and Neural Computing and Applications. He is also serving as Associate Editor of Circuits Systems and Signal Processing (CSSP) and Computer journals.

Notes: The focus of the session should be practical (learning by doing principle) to enhance the learning relevance to workshop

participants. 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.