HKR 6000 Quantitative Methods in Physical Education
Instructor
Dr. Daniel Fuller
E-mail
- dfuller@mun.ca
Office
- PE2023
Office Hours
Time
- Synchronous - Mondays from 9:30-10:30am (NL time)
- Asynchronous - 1 hour video per week
Location
- The internet
Prerequisites
None
Course Description
A critical examination of methodological research issues and quantitative research designs in the field of human kinetics and recreation. Examines and applies a variety of statistical analysis techniques which can be used in a variety of research designs. Emphasis is placed on the interpretation and implications of empirical quantitative research in the field. Students will learn statistics using either R or SPSS.
Course Objectives
- To introduce students to the nature of scientific inquiry and techniques of research design;
- To examine the prevalent methods and techniques of quantitative research design;
- To provide you with the understanding and knowledge necessary for refining your skills as competent researchers;
- To introduce the basics of analysis and interpretation of statistical measures, techniques, and tests, in order to provide the student with an understanding of their application human kinetics and recreation;
- To present an overview of the most commonly used descriptive statistics and inferential parametric and statistical measures and tests within human kinetics and recreation;
- To assess under what circumstances certain analytical techniques are selected and why, and to recognise the strengths and weaknesses of these decisions; and
- To afford the opportunity for computer-based applications of different procedures and techniques described in class thereby providing “hands on” experience for a practical understanding of the organisation and construction of data and measures, the selection of appropriate techniques, and the analysis and interpretation of “real” results.
Format and Procedures
The general format of each week will include one asynchronous video discussing the key concepts for the week, one sychronous session working through applied problems related to the weeks content and on assignment to apply new knowledge.
This course will use this website and D2L as the method for course communication and to provide students with course materials (e.g., syllabus, handouts, instructions for assignments, readings, and course schedule). The course materials that are needed for each class will be posted on D2L a minimum of one (1) week prior to the class date.
Course Text
- Fields, A. (2010). Discovering Statistics Using SPSS (3rd ed). London, England: Sage Publications.
OR
- Fields, A. (2013). Discovering Statistics Using SPSS (4th ed). London, England: Sage Publications.
Additional readings are required. These readings will be in electronic format and will be posted on D2L. Readings will be available at least one (1) weeks prior to the reading assignment due date.
Academic Integrity
Students and faculty at Memorial University share an important responsibility to maintain the integrity of the teaching and learning relationship. This relationship is characterized by honesty, fairness and mutual respect for the aim and principles of the pursuit of education.
Academic misconduct impedes the activities of the university community and is punishable by appropriate disciplinary action. Students are expected to be familiar with Memorial University’s regulations on Academic Misconduct (Section 6.12 of the Academic Calendar) which sets out the kinds of actions that constitute academic misconduct, including plagiarism, copying or allowing one’s own work to copied, use of unauthorized aids in examinations and tests, submitting work prepared in collaboration with another student when such collaboration has not been authorized, and other academic offenses. The regulations also describe the procedures for dealing with allegations and the unit level as well as the university level, and the sanctions for any finding of academic misconduct, which can range from a written reprimand to a rescindment of the degree. A lack of familiarity with Memorial’s regulations on academic misconduct does not constitute a defense against its application.
If an instructor alleges that academic misconduct has occurred for evaluative instruments worth between 15-39% the course instructor is required to submit the student’s work along with a summary of the allegation to the SHKR Committee for Academic Integrity for consideration and a decision. Any allegations of misconduct that occur with evaluative instruments worth 40% or more of the final grade or final examinations are automatically sent to the Senate Committee on Undergraduate Studies for consideration.
Further information on academic integrity is outlined in the University Calendar 6.12: http://www.mun.ca/regoff/calendar/sectionNo=REGS-0748 Information regarding acceptable writing practices is available through the Writing Centre at http://www.mun.ca/writingcentre/
Accommodations for students with disabilities
In compliance with the Memorial University’s policy and equal access laws, it is understood that appropriate academic accommodations may be required for student with disabilities. Please see the guide for full details http://www.mun.ca/policy/site/policy.php?id=239.
Methods of assessment
| Assignment | Percent | Due Date |
|---|---|---|
| Quizzes | 10% | See below |
| Satistics Assignments | 40% | See below |
| Exploratory Data Analysis Part 1 | 10% | March 12 |
| Exploratory Data Analysis Part 2 | 20% | April 9 |
| Final Exam | 20% | TBA |
Note 1. I purposefuly do not have penalties for late assignments. You will have the most success with this course if you submit the assignments on time. There will be a steep learning curve. It will hurt. The faster you get over the learning curve, the easier, and more fun, your life will be in this course.
Note 2. There are no specific formatting rules or guidelines for the course. Use some type of reference formatting, APA and AMA are good choices.
Quizzes
Students will be required to complete a total of five (5) quizzes (weighted equally) based on the textbook readings for the course (see table below). Quizzes are to be completed on D2L before class on the due date. See table below for topics, associated readings, and due dates. Quizzes will be open book (i.e., you are allowed to have the textbook and any notes you make in front of you); however, you are not permitted to use any other resources or speak to any person (electronically or verbally) while completing the quiz. To prepare for the quiz read the appropriate chapter and make some notes for key points so that you can easily locate the answers while completing the quiz. Quizzes will generally consist of approximately 10 multiple choice questions and you will be allowed approximately 45 minutes (so you will have lots of time to complete the open book quiz). The first quiz consists of 15 multiple choice questions and you are allowed 60 minutes. If you have any technical problems while completing the quiz, please contact the instructor immediately via email.
| Number | Topic | Edition & Chapter | Grade % |
|---|---|---|---|
| Q1 | Statistics Review | 3rd and 4th Edition Chapter 1 and 2 | 2 |
| Q2 | Exploring Data | 3rd and 4th Edition Chapter 4 and 5 | 2 |
| Q3 | Correlation | 3rd Edition Chapter 6, 4th Edition Chapter 7 | 2 |
| Q4 | Regression | 3rd Edition Chapter 7, 4th Edition Chapter 8 | 2 |
| Q5 | ANOVA | 3rd Edition Chapter 10, 4th Edition Chapter 11 | 2 |
Statistics Assignments
Students will be required to complete six (6) statistical assignments. Further details of the assignment will be provided in class and on D2L. Statistics Assignments are to be submitted via the appropriate D2L dropbox by 5:00pm on the due date. See table below for topics, associated readings, and due dates.
| Number | Topic | Description | Code Sample | Grade % |
|---|---|---|---|---|
| A1 | SPSS or R Environment | Description | R - SPSS | 3 |
| A2 | Exploring Data | Description | R - SPSS | 7 |
| A3 | Comparing means | Description | R - SPSS | 5 |
| A4 | Regression | Description | R - SPSS | 9 |
| A5 | ANOVA | Description | R - SPSS | 7 |
| A6 | Repeated Measures | Description | R - SPSS | 9 |
Major Written Assignment
Students are required to complete the final assignment.
Conduct an exploratory data analysis and write up your findings in the form of a detailed draft formatted for a potential target journal in your field. You can select from one of the provided datasets below or select one of your own datasets. Data sets (if not using supplied data) and a project proposal must be approved by the instructor. Students are encouraged to consult with the instructor and with their supervisor related to using a specific dataset. Minimum page length is 8 pages (~2000 words) and maximum is 15 (~3600 words) not including references and tables.
The exploratory data analysis should include
- Introduction/literature review (~500 words)
- Method (~800 words)
- Design
- Data
- Analysis plan
- Results (~1000)
- Descriptive statistics
- Inferential statistics
- Discussion/conclusions (~500 words)
The assignment will be completed/submitted in 2 Parts
1. Part 1 consists of submitting a 4 page draft. (10% of course grade)
2. Part 2 consists of submitting the final paper. (20% of course grade)
Final Exam
Students will compelte an online final exam focussing on methodology and statistical topics/analysis learned throughout the course. Part A of the exam will first consist of multiple choice and short answers. Part B of the exam will be open book and will include the anlaysis of a data set.
Weekly Schedule
| Week | Date | Theme | Topic | Assignment | Due Date |
|---|---|---|---|---|---|
| Week 1 | January 11 | Statistics | Intro | Q1 | Janury 15 |
| Week 2 | January 18 | Methods | Research Design | A1 | Janury 22 |
| Week 3 | January 25 | Methods | Quantitative Measurement | Q2, A2 | Janury 29 |
| Week 4 | February 1 | Methods | Research and Analysis Design | ||
| Week 5 | February 8 | Statistics | Correlation | Q3 | February 12 |
| Week 6 | February 15 | Statistics | Linear Regression | A3 | February 19 |
| Week 7 | February 22 | Reading Week | |||
| Week 8 | March 1 | Statistics | Comparing Means & ANOVA | Q4, A4 | March 5 |
| Week 9 | March 8 | Statistics | Repeated Measures | Final Assignment Part 1 | March 12 |
| Week 10 | March 15 | Statistics | Non Parametric Methods | Q5, A5 | March 19 |
| Week 11 | March 22 | Statistics | Data Visualization | A6 | March 26 |
| Week 12 | March 29 | Review | All The Things | Final Assignment Part 2 | April 9 |