Twin Cities campus

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Twin Cities Campus

Kinesiology Ph.D.

Kinesiology, School of
College of Education and Human Development
Link to a list of faculty for this program.
Contact Information
School of Kinesiology, 1900 University Avenue S.E., Minneapolis, MN 55455 (612-625-5300; fax: 612-626-7700)
Email: kin@umn.edu
Website: http://cehd.umn.edu/kin
  • Program Type: Doctorate
  • Requirements for this program are current for Fall 2015
  • Length of program in credits: 60 to 72
  • This program does not require summer semesters for timely completion.
  • Degree: Doctor of Philosophy
Along with the program-specific requirements listed below, please read the General Information section of this website for requirements that apply to all major fields.
Ph.D. students pursue an individualized program with an emphasis in biomechanics and neuromotor control, exercise physiology, perceptual-motor control and learning, physical activity and sport science, or sport management.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
Prerequisites for Admission
The preferred undergraduate GPA for admittance to the program is 3.00.
It is preferred that applicants have completed a master's degree in the field of kinesiology or a related field and achieved an overall minimum GPA of 3.50.
Other requirements to be completed before admission:
Applicants must have completed a baccalaureate degree, generally in the following areas: kinesiology; exercise science; sport management; sport psychology/sociology; movement science; or related preparation and significant background and interest in the scientific study of physical activity.
Special Application Requirements:
Applicants must submit a University of Minnesota application which includes a written statement of academic interests, goals, and objectives; scores from the General Test of the GRE (verbal, quantitative, and analytical writing) that are less than five years old; three recommendations from persons familiar with their scholarship and research potential; a scholarly writing sample; and transcripts. Submission of all application materials by December 15 ensures priority consideration for admission and for teaching and research assistantships awarded for the next academic year. Students are admitted for the fall semester.
Applicants must submit their test score(s) from the following:
  • GRE
    • General Test - Verbal Reasoning: 153
    • General Test - Quantitative Reasoning: 153
    • General Test - Analytical Writing: 4.5
International applicants must submit score(s) from one of the following tests:
  • TOEFL
    • Internet Based - Total Score: 79
    • Internet Based - Listening Score: 14
    • Internet Based - Writing Score: 21
    • Internet Based - Reading Score: 19
    • Internet Based - Speaking Score: 23
    • Paper Based - Total Score: 550
  • IELTS
    • Total Score: 6.5
  • MELAB
    • Final score: 80
The preferred English language test is Test of English as Foreign Language.
Key to test abbreviations (GRE, TOEFL, IELTS, MELAB).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
24 to 29 credits are required in the major.
12 to 19 credits are required outside the major.
24 thesis credits are required.
This program may be completed with a minor.
Use of 4xxx courses towards program requirements is not permitted.
A minimum GPA of 3.00 is required for students to remain in good standing.
The Ph.D. requires 36 to 48 course credits and 24 thesis credits. A minimum total of 60 credits and a maximum total of 72 credits are required to complete the program. Course credits include a minimum of 15 major program credits (including 3 credits of KIN 8980 Graduate Research Seminar), 6 credits in a supporting program or 12 credits in a doctoral minor, 6 research skills course credits, and 9 credits of mentored research experience. At least 6 major course credits, 6 research skills course credits, and 6 mentored experience course credits must be taken as a U of MN enrolled student. A GPA of at least 3.00 is required to maintain good standing and to graduate.
Required Kinesiology Courses
A minimum of 3 credits of KIN 8980 and a minimum of 9 credits of KIN 8995 are required over the course of the program.
KIN 8980 - Graduate Research Seminar in Kinesiology (3.0 cr)
KIN 8995 - Research Problems in Kinesiology (1.0-12.0 cr)
Emphasis Areas
Kinesiology Ph.D. students pursue an individualized program with an emphasis in biomechanics and neuromotor control, exercise physiology, perceptual-motor control and learning, physical activity and sport science, or sport management.
Biomechanics and Neuromotor Control
The study of the mechanical and electromyographic analysis of human motion is combined with neurophysiological knowledge about the various neuronal subsystems to provide a basis for understanding how the brain controls bodily and limb motion.
Emphasis courses
A minimum of 12 course credits must be selected from the following list. At least 3 credits must be KIN 8xxx.
KIN 5235 - Advanced Biomechanics II: Kinetics (3.0 cr)
or KIN 5941 - Clinical Movement Neuroscience (3.0 cr)
or KIN 8211 - Seminar: Perception and Action (3.0 cr)
or KIN 8132 - Seminar: Motor Development (3.0 cr)
or KIN 8135 - Seminar: Motor Control and Learning (3.0 cr)
or RSC 5135 - Advanced Biomechanics I: Kinematics (3.0 cr)
or RSC 5841 - Applied Data Acquisition and Processing (3.0 cr)
or NSC 5661 - Behavioral Neuroscience (2.0 cr)
Research skills courses
A minimum of 6-9 research skills course credits are required, selected from the following list or in consultation with the adviser. Courses taken to fulfill the research skills courses requirement can't be double counted to fulfill the supporting program requirement.
EPSY 8261 {Inactive} (3.0 cr)
or EPSY 8262 {Inactive} (3.0 cr)
or EPSY 8264 - Advanced Multiple Regression Analysis (3.0 cr)
or EPSY 8267 - Applied Multivariate Analysis (3.0 cr)
or PUBH 6450 - Biostatistics I (4.0 cr)
or PUBH 6451 - Biostatistics II (4.0 cr)
or PUBH 7405 - Biostatistical Inference I (4.0 cr)
or PUBH 7406 - Biostatistical Inference II (3.0 cr)
or STAT 5021 - Statistical Analysis (4.0 cr)
or STAT 5302 - Applied Regression Analysis (4.0 cr)
or STAT 5303 - Designing Experiments (4.0 cr)
or STAT 5601 - Nonparametric Methods (3.0 cr)
Minor
Choose either minor or supporting program. A minimum of 12 course credits are required for a University of Minnesota doctoral minor. Recommended minors include: CGSC, CPMS, GERO, HUMF, NSC, or PREV.
Supporting program
Any combination of at least 6 KIN or non-KIN course credits may be used for the supporting program and must be approved by the adviser. Recommended Kinesiology emphasis areas for supporting courses include Exercise Physiology, Perceptual-Motor Control and Learning, Physical Activity and Sport Science, or Sport Management. Recommended program areas for supporting courses include: BMEN, ME, NURS, OT, OTOL, PubH, NSC and RSC.
KIN 5981 - Research Methodology in Kinesiology and Sport Management (3.0 cr)
or KIN 5987 - Professional Skills and Grant Writing for Health Sciences (2.0 cr)
-OR-
Exercise Physiology
Exercise physiology is the study of issues related to acute and chronic effects of physical activity on human physiological systems and health, and how fundamental concepts of human energetics and mechanics apply to exercise, sport, physical exertion, and health promotion. Doctoral students learn to apply principles of physiology to solving problems related to functional responses and adaptations involved in human skeletal muscular activity.
Emphasis courses
A minimum of 12 course credits must be selected from the following list. At least 3 credits must be KIN 8xxx. KIN 8122 may be taken multiple times.
KIN 5122 - Applied Exercise Physiology (3.0 cr)
or KIN 5141 - Nutrition and Exercise for Health Promotion and Disease Prevention (3.0 cr)
or KIN 5142 - Applied Nutrition for Sport Performance and Optimal Health (3.0 cr)
or KIN 5385 - Exercise for Healthy Aging & Disease Prevention and Management (3.0 cr)
or KIN 5435 - Advanced Theory and Techniques of Exercise Science (3.0 cr)
or KIN 5485 - Exercise Testing and Prescription (3.0 cr)
or KIN 5585 {Inactive} (2.0 cr)
or KIN 5641 - Scientific Theory and Application of Training and Conditioning in Sport (3.0 cr)
or KIN 5720 - Special Topics in Kinesiology (2.0-4.0 cr)
or KIN 5987 - Professional Skills and Grant Writing for Health Sciences (2.0 cr)
or KIN 8122 - Seminar: Exercise Physiology (2.0 cr)
Research skills courses
A minimum of 6-9 research skills course credits are required, selected from the following list or in consultation with the adviser. It is recommended to take a statistical sequence in either EPSY, STAT, or PubH. It is not recommended to switch courses between departments unless agreed to by the adviser. Courses taken to fulfill the research skills courses requirement can't be double counted to fulfill the supporting program requirement.
EPSY 8261 {Inactive} (3.0 cr)
or EPSY 8262 {Inactive} (3.0 cr)
or EPSY 8264 - Advanced Multiple Regression Analysis (3.0 cr)
or EPSY 8267 - Applied Multivariate Analysis (3.0 cr)
or PUBH 6450 - Biostatistics I (4.0 cr)
or PUBH 6451 - Biostatistics II (4.0 cr)
or PUBH 7405 - Biostatistical Inference I (4.0 cr)
or PUBH 7406 - Biostatistical Inference II (3.0 cr)
or PUBH 7415 - Introduction to Clinical Trials (3.0 cr)
or PUBH 7430 - Statistical Methods for Correlated Data (3.0 cr)
or STAT 5021 - Statistical Analysis (4.0 cr)
or STAT 5302 - Applied Regression Analysis (4.0 cr)
or STAT 5303 - Designing Experiments (4.0 cr)
or STAT 5601 - Nonparametric Methods (3.0 cr)
Minor
Choose either a minor or supporting program. A minimum of 12 course credits are required for a University of Minnesota doctoral minor. Recommended minors include: CGSC, CPMS, GERO, HUMF, NSC, or PREV.
Supporting program
Any combination of at least 6 KIN or non-KIN course credits may be used for the supporting program and must be approved by the adviser. Recommended Kinesiology emphasis areas for supporting courses include Biomechanics and Neuromotor Control, Perceptual-Motor Control and Learning, Physical Activity and Sport Science, or Sport Management. Recommended areas for supporting program include: BIOC, FSCN, OT, PHSL, PubH, NSC, and RSC.
-OR-
Perceptual-Motor Control and Learning
Perceptual-motor control and learning includes related areas of movement behavior inquiry. Motor learning is the study of the learning of movement skills and the factors that mediate learning, such as practice, perceptual guidance, or knowledge of results. Although a lifespan approach is emphasized, students may focus on one or more specific age periods, such as infancy, early childhood, adolescence, or later adulthood.
Emphasis courses
A minimum of 12 course credits must be selected from the following list. At least 3 credits must be KIN 8xxx.
KIN 5235 - Advanced Biomechanics II: Kinetics (3.0 cr)
or KIN 5941 - Clinical Movement Neuroscience (3.0 cr)
or KIN 8211 - Seminar: Perception and Action (3.0 cr)
or KIN 8132 - Seminar: Motor Development (3.0 cr)
or KIN 8135 - Seminar: Motor Control and Learning (3.0 cr)
or RSC 5135 - Advanced Biomechanics I: Kinematics (3.0 cr)
or RSC 5841 - Applied Data Acquisition and Processing (3.0 cr)
Research skills courses
A minimum of 6-9 research skills course credits are required, selected from the following list or in consultation with the adviser. It is recommended to take a statistical sequence in either EPSY, STAT, or PubH. It is not recommended to switch courses between departments unless agreed to by the adviser. Courses taken to fulfill the research skills courses can't be double counted to fulfill the supporting program requirement.
EPSY 8261 {Inactive} (3.0 cr)
or EPSY 8264 - Advanced Multiple Regression Analysis (3.0 cr)
or EPSY 8267 - Applied Multivariate Analysis (3.0 cr)
or EPSY 8282 - Statistical Analysis of Longitudinal Data (3.0 cr)
or PUBH 6450 - Biostatistics I (4.0 cr)
or PUBH 6451 - Biostatistics II (4.0 cr)
or PUBH 7405 - Biostatistical Inference I (4.0 cr)
or PUBH 7406 - Biostatistical Inference II (3.0 cr)
or STAT 5201 - Sampling Methodology in Finite Populations (3.0 cr)
or STAT 5302 - Applied Regression Analysis (4.0 cr)
or STAT 5303 - Designing Experiments (4.0 cr)
or STAT 5601 - Nonparametric Methods (3.0 cr)
Minor
Choose either a minor or supporting program. All University of Minnesota doctoral minors require a minimum of 12 credits. Recommended minors include CGSC, CPMS, GERO, HUMF, NSC, or PREV.
Supporting program
Any combination of at least 6 KIN or non-KIN course credits may be used for the supporting program and must be approved by the adviser. Recommended Kinesiology emphasis areas for supporting courses include Biomechanics and Neuromotor Control, Exercise Physiology, Physical Activity and Sport Science, or Sport Management. Recommended programs for supporting courses include: BMEN, ME, NURS, OT, OTOL, PubH, NSC, and RSC. Specific KIN course recommendations include:
KIN 5981 - Research Methodology in Kinesiology and Sport Management (3.0 cr)
or KIN 5987 - Professional Skills and Grant Writing for Health Sciences (2.0 cr)
-OR-
Physical Activity and Sport Science
This emphasis centers on the broad context of human physical activity in areas such as competitive sport, fitness programs, lifestyle exercise, physical education, sports medicine and physical rehabilitation. Students can choose from three concentrations: behavioral aspects of physical activity, sport and exercise psychology, and sport sociology.
Emphasis courses
A minimum of 12 course credits must be selected from the following list. At least 3 credits must be KIN 8xxx. KIN 5720 is limited to 3 credits. Course credits for KIN 8696 determined in consultation with adviser.
KIN 5123 - Motivational Interventions in Physical Activity (3.0 cr)
or KIN 5126 - Social Psychology of Sport & Physical Activity (3.0 cr)
or KIN 5136 - Psychology of Coaching (3.0 cr)
or KIN 5371 - Sport and Society (3.0 cr)
or KIN 5375 {Inactive} (3.0 cr)
or KIN 5720 - Special Topics in Kinesiology (2.0-4.0 cr)
or KIN 5511 - Sport and Gender (3.0 cr)
or KIN 5723 - Psychology of Sport Injury and Rehabilitation (3.0 cr)
or KIN 8126 - Sports Medicine Psychology (3.0 cr)
or KIN 8136 - Developmental Sport and Exercise Psychology (3.0 cr)
or KIN 8696 {Inactive} (3.0-6.0 cr)
Research skills courses
A minimum of 6-9 research skills course credits are required, selected from the following list or in consultation with the adviser. Courses taken to fulfill the research skills credits can't be double counted to fulfill the supporting program requirement.
KIN 5981 - Research Methodology in Kinesiology and Sport Management (3.0 cr)
or EPSY 5247 - Qualitative Methods in Educational Psychology (3.0 cr)
or EPSY 8247 {Inactive} (3.0 cr)
or EPSY 8261 {Inactive} (3.0 cr)
or EPSY 8262 {Inactive} (3.0 cr)
or EPSY 8264 - Advanced Multiple Regression Analysis (3.0 cr)
or EPSY 8266 - Statistical Analysis Using Structural Equation Methods (3.0 cr)
or EPSY 8267 - Applied Multivariate Analysis (3.0 cr)
or EPSY 8282 - Statistical Analysis of Longitudinal Data (3.0 cr)
or PSY 8209 - Research Methods in Social Psychology (3.0 cr)
or PUBH 6810 - Survey Research Methods (3.0 cr)
or PUBH 7401 - Fundamentals of Biostatistical Inference (4.0 cr)
or PUBH 7405 - Biostatistical Inference I (4.0 cr)
or PUBH 7406 - Biostatistical Inference II (3.0 cr)
Minor
Choose either a minor or supporting program. A minimum of 12 course credits are required for a University of Minnesota doctoral minor. Recommended minors include: EPSY, PREV, PSY, PUBH, SOC, or Integrative Therapies and Healing Practices offered by the Center for Spirituality and Healing.
Supporting program
Any combination of at least 6 KIN or non-KIN course credits may be used for the supporting program and must be approved by the adviser. Recommended concentrations for supporting courses include Behavioral Aspects of Physical Activity, Sport and Exercise Psychology, or Sport Sociology. Students should consult with their adviser for program guidance. Specific KIN course recommendations include:
KIN 5725 - Organization and Management of Physical Education and Sport (3.0 cr)
or KIN 5801 - Legal Aspects of Sport and Physical Activity (4.0 cr)
-OR-
Sport Management
This emphasis concentrates on the theoretical and practical dimensions of the management of athletic events, sports teams and facilities, and the sporting process. The management areas studied include those in the public sector (interscholastic and intercollegiate sport) as well as fitness and facility management. Sport management policy and ethics are also a focus of this emphasis area and research agenda.
Required courses
The following courses are required for a total of 6 credits. Students will take three registrations of KIN 8980 for 1 credit each.
KIN 8980 - Graduate Research Seminar in Kinesiology (3.0 cr)
KIN 8128 - Doctoral Sport Management Seminar (3.0 cr)
Program courses
A minimum of 9 credits must be selected from the following list:
KIN 5111 - Sports Facilities (3.0 cr)
or KIN 5375 {Inactive} (3.0 cr)
or KIN 5511 - Sport and Gender (3.0 cr)
or KIN 5371 - Sport and Society (3.0 cr)
or KIN 5421 - Sport Finance (3.0 cr)
or KIN 5461 - Issues in the Sport Industry (3.0 cr)
or KIN 5601 - Sport Management Ethics and Policy (3.0 cr)
or KIN 5631 - Programming and Promotion in Sport (3.0 cr)
or KIN 5725 - Organization and Management of Physical Education and Sport (3.0 cr)
or KIN 5801 - Legal Aspects of Sport and Physical Activity (4.0 cr)
Research skills courses
A minimum of 6-9 research skills course credits are required, selected from the following list or in consultation with the adviser. Courses taken to fulfill the research skills courses requirement can't be double counted to fulfill the supporting program requirement.
KIN 5981 - Research Methodology in Kinesiology and Sport Management (3.0 cr)
or OLPD 5056 - Case Studies for Policy Research (3.0 cr)
or OLPD 5061 - Ethnographic Research Methods (3.0 cr)
or OLPD 5528 {Inactive} (1.0-3.0 cr)
or EPSY 5247 - Qualitative Methods in Educational Psychology (3.0 cr)
or EPSY 8247 {Inactive} (3.0 cr)
or EPSY 8264 - Advanced Multiple Regression Analysis (3.0 cr)
or EPSY 8265 - Factor Analysis (3.0 cr)
or EPSY 8266 - Statistical Analysis Using Structural Equation Methods (3.0 cr)
or EPSY 8267 - Applied Multivariate Analysis (3.0 cr)
or FSOS 8013 - Qualitative Family Research Methods (3.0 cr)
Minor
Choose either a minor or supporting program. A minimum of 12 course credits are required for a University of Minnesota doctoral minor. Recommended minors include: Public Policy, COMM, EPSY, BA, or CI.
Supporting program
Any combination of at least 6 KIN or non-KIN course credits may be used for the supporting program and must be approved by the adviser. Recommended Kinesiology emphasis areas for supporting courses include Biomechanics and Neuromotor Control, Exercise Physiology, Physical Activity and Sport Science, and Perceptual- Motor Control and Learning. Recommended program areas for supporting program courses include: OLPD, PA, COMM, Marketing, and Management.
 
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KIN 8980 - Graduate Research Seminar in Kinesiology
Credits: 3.0 [max 9.0]
Grading Basis: A-F only
Typically offered: Every Fall
Reporting/discussion of student/faculty research activity. prereq: KIN M.S. or Ph.D. or SMGT M.A. or instr consent
KIN 8995 - Research Problems in Kinesiology
Credits: 1.0 -12.0 [max 12.0]
Grading Basis: S-N only
Typically offered: Every Fall, Spring & Summer
Individual scholarly research. prereq: Kin Ph.D. student or SMGT grad student or instr consent
KIN 5235 - Advanced Biomechanics II: Kinetics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
Kinetic aspects of human movement (single/multi-joint torques, simple inverted pendulum models, mass-spring systems). Analysis of experimental data and of computer simulations. Lectures, seminars, lab. prereq: [3112 or equiv], PMed 5135, undergrad college physics, intro calculus
KIN 5941 - Clinical Movement Neuroscience
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Periodic Spring
Various neural subsystems involved in controlling human motor function. How injury and disease of the nervous system affects motor behavior. Possibilities for rehabilitation and treatment. Lectures, seminars, class presentations. prereq: [3027 or ANAT 3001 or ANAT 3601 or ANAT 3611 or equiv], [PHSL 3051 or equiv], [4441]
KIN 8211 - Seminar: Perception and Action
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Survey of theory/research on use of perceptual information for control of action. Behavioral research on perceptual guidance of daily activities (e.g., standing, walking, driving). Perceptual control in context of expertise (e.g., sports). Perceptual-motor development. prereq: grad student or instr consent
KIN 8132 - Seminar: Motor Development
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Contemporary research literature on motor skill development from before birth to senescence. Emphasizes interaction between physical/environmental/performer constraints. Coordination/control of movement. prereq: grad student or instr consent
KIN 8135 - Seminar: Motor Control and Learning
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Advanced reading/discussion of research on motor control, motor learning, human performance. prereq: grad student or instr consent
RSC 5135 - Advanced Biomechanics I: Kinematics
Credits: 3.0 [max 3.0]
Course Equivalencies: RSc 5135/RSc 8135
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
How to describe/measure movement. Basic/applied biomechanics, pathokinesiology, and rehabilitation literature. Lecture, lab, seminar discussion. Meets with RSC 8135. prereq: instr consent
RSC 5841 - Applied Data Acquisition and Processing
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
This course will introduce students to collecting and processing biomedical time series data. Students will gain experience using data acquisition hardware common in many laboratories, as well as related software for acquisition of the data and digital signal processing. Data sources will include electromyography (EMG), wearable sensors, motion capture, and data from other systems based on the background and interests of students in the class. The overall goal of this course is to provide students with the necessary, fundamental skills to run a successful experiment, troubleshoot errors, and produce high quality data sets. prereq: prefer students to have completed general physics, introductory of short calculus
NSC 5661 - Behavioral Neuroscience
Credits: 2.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Neural coding/representation of movement parameters. Neural mechanisms underlying higher order processes such as memorization, memory scanning, and mental rotation. Emphasizes experimental psychological studies in human subjects, single cell recording experiments in subhuman primates, and artificial neural network modeling. prereq: Grad NSc major or grad NSc minor or instr consent
EPSY 8264 - Advanced Multiple Regression Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
General linear model used as context for regression. Matrix algebra, multiple regression, path analysis, polynomial regression, standardized regression, stepwise solutions, analysis of variance, weighted least squares, logistic regression. prereq: [8252 or equiv], regression/ANOVA course, familiarity with statistical analysis package
EPSY 8267 - Applied Multivariate Analysis
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Use/interpretation of results from several multivariate statistical techniques. Matrix algebra, variance/covariance, Hotelling's T2, GLM, MANOVA, MANCOVA, discriminant analysis, canonical correlations, dimensionality, principal components, latent composites, distance, hierarchical clustering. prereq: [8252 or equiv], familiarity with matrix algebra, knowledge of a computerized statistics package
PUBH 6450 - Biostatistics I
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
This course will cover the fundamental concepts of exploratory data analysis and statistical inference for univariate and bivariate data, including: ? study design and sampling methods, ? descriptive and graphical summaries, ? random variables and their distributions, ? interval estimation, ? hypothesis testing, ? relevant nonparametric methods, ? simple regression/correlation, and ? introduction to multiple regression. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [College-level algebra, health sciences grad student] or instr consent
PUBH 6451 - Biostatistics II
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
This course will cover more advanced aspects of statistical analysis methods with a focus on statistical modeling, including: ? two-way ANOVA, ? multiple linear regression, ? logistic regression, ? Poisson regression, ? log binomial and ordinal regression, ? survival analysis methods, including Kaplan-Meier analysis and proportional hazards (Cox) regression, ? power and sample size, and ? survey sampling and analysis. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [PubH 6450 with grade of at least B, health sciences grad student] or instr consent
PUBH 7405 - Biostatistical Inference I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
T-tests, confidence intervals, power, type I/II errors. Exploratory data analysis. Simple linear regression, regression in matrix notation, multiple regression, diagnostics. Ordinary least squares, violations, generalized least squares, nonlinear least squares regression. Introduction to General linear Model. SAS and S-Plus used. prereq: [[Stat 5101 or concurrent registration is required (or allowed) in Stat 5101], biostatistics major] or instr consent
PUBH 7406 - Biostatistical Inference II
Credits: 3.0 [max 4.0]
Typically offered: Every Spring
This course introduces students to a variety of concepts, tools, and techniques that are relevant to the rigorous design and analysis of complex biomedical studies. Topics include ANOVA, sample-size calculations, multiple testing, missing data, prediction, diagnostic testing, smoothing, variable selection, the bootstrap, and nonparametric tests. R software will be used. Biostatistics students are strongly encouraged to typeset their work using LaTeX or in R markdown. prereq: [7405, [STAT 5102 or concurrent registration is required (or allowed) in STAT 5102], biostatistics major] or instr consent
STAT 5021 - Statistical Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Intensive introduction to statistical methods for graduate students needing statistics as a research technique. prereq: college algebra or instr consent; credit will not be granted if credit has been received for STAT 3011
STAT 5302 - Applied Regression Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications. prereq: 3032 or 3022 or 4102 or 5021 or 5102 or instr consent Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.
STAT 5303 - Designing Experiments
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Analysis of variance. Multiple comparisons. Variance-stabilizing transformations. Contrasts. Construction/analysis of complete/incomplete block designs. Fractional factorial designs. Confounding split plots. Response surface design. prereq: 3022 or 3032 or 3301 or 4102 or 5021 or 5102 or instr consent
STAT 5601 - Nonparametric Methods
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Order statistics. Classical rank-based procedures (e.g., Wilcoxon, Kruskal-Wallis). Goodness of fit. Topics may include smoothing, bootstrap, and generalized linear models. prereq: Stat classes 3032 or 3022 or 4102 or 5021 or 5102 or instr consent
KIN 5981 - Research Methodology in Kinesiology and Sport Management
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Defines/reviews various types of research in exercise/sport science, and physical education. Qualitative research, field studies, and methods of introspection as alternative research strategies to traditional scientific paradigm.
KIN 5987 - Professional Skills and Grant Writing for Health Sciences
Credits: 2.0 [max 2.0]
Grading Basis: OPT No Aud
Typically offered: Spring Odd Year
Introduction to structure/function of different organizations (e.g., NIH, AHA). Writing/reviewing grants/manuscripts. Preparing for a job in academia. prereq: Grad student
KIN 5122 - Applied Exercise Physiology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Mechanisms of cardiorespiratory and muscular responses to exercise; application of exercise physiology to assessment of work capacity, athletic conditioning, and requirements of human powered vehicles; low to moderate exercise as an intervention in lowering risk for common health problems. prereq: 4385 or equiv or instr consent
KIN 5141 - Nutrition and Exercise for Health Promotion and Disease Prevention
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Requirements/physiologic roles of nutrients/physical activity in promotion of health. Assessment of energy requirements. RDAs, food composition/safety, weight management. Prevention of chronic diseases. Coronary heart disease. prereq: FScN 1112 or equiv
KIN 5142 - Applied Nutrition for Sport Performance and Optimal Health
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring
This course is designed for students interested in nutrition as it relates to health, exercise and athletic training. Evidenced based information is used to apply current nutrition concepts to improve health, physical and athletic performance. Case studies as well as personal data are employed throughout course to support concepts of lecture.
KIN 5385 - Exercise for Healthy Aging & Disease Prevention and Management
Credits: 3.0 [max 3.0]
Prerequisites: Physiology or biology undergrad
Grading Basis: A-F only
Typically offered: Every Spring
Exercise testing/prescription with modifications required because of special considerations associated with aging, gender differences, or presence of medical conditions. prereq: Physiology or biology undergrad
KIN 5435 - Advanced Theory and Techniques of Exercise Science
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring
Theoretical constructs, in-depth description of procedures used in exercise science research and clinical settings. Laboratory exercises, lectures. prereq: [3385, 4385, Kin major] or instr consent
KIN 5485 - Exercise Testing and Prescription
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
This course will provide an introduction to exercise testing and prescription including basic placement of EKG placement and interpretation of an electrocardiogram. Students will also learn the basics of gas exchange and fitness test and the use of this information in the prescription of exercise in a variety of populations as well as use of electrocardiogram in clinical exercise testing and exercise prescription. prereq: [3385, 4385] or instr consent
KIN 5641 - Scientific Theory and Application of Training and Conditioning in Sport
Credits: 3.0 [max 3.0]
Prerequisites: 4385 or SPST 3641 or SPST 4641 or exercise physiology course or #
Grading Basis: A-F only
Typically offered: Every Spring & Summer
Current scientific literature on physiological adaptation through training/conditioning for sport. Applying methods in research journals to improve physiological adaptation through training/conditioning with sport specificity. prereq: 4385 or SPST 3641 or SPST 4641 or exercise physiology course or instr consent
KIN 5720 - Special Topics in Kinesiology
Credits: 2.0 -4.0 [max 12.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Current issues in the broad field and subfields in kinesiology, or related coursework in areas not normally available through regular offerings.
KIN 5987 - Professional Skills and Grant Writing for Health Sciences
Credits: 2.0 [max 2.0]
Grading Basis: OPT No Aud
Typically offered: Spring Odd Year
Introduction to structure/function of different organizations (e.g., NIH, AHA). Writing/reviewing grants/manuscripts. Preparing for a job in academia. prereq: Grad student
KIN 8122 - Seminar: Exercise Physiology
Credits: 2.0 [max 8.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Classic/contemporary literature in exercise physiology/allied disciplines. Contributions of major leaders in field. Opportunities for interdisciplinary research. Spring semester students/faculty in exercise science present original research. prereq: 5122 or equiv or instr consent
EPSY 8264 - Advanced Multiple Regression Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
General linear model used as context for regression. Matrix algebra, multiple regression, path analysis, polynomial regression, standardized regression, stepwise solutions, analysis of variance, weighted least squares, logistic regression. prereq: [8252 or equiv], regression/ANOVA course, familiarity with statistical analysis package
EPSY 8267 - Applied Multivariate Analysis
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Use/interpretation of results from several multivariate statistical techniques. Matrix algebra, variance/covariance, Hotelling's T2, GLM, MANOVA, MANCOVA, discriminant analysis, canonical correlations, dimensionality, principal components, latent composites, distance, hierarchical clustering. prereq: [8252 or equiv], familiarity with matrix algebra, knowledge of a computerized statistics package
PUBH 6450 - Biostatistics I
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
This course will cover the fundamental concepts of exploratory data analysis and statistical inference for univariate and bivariate data, including: ? study design and sampling methods, ? descriptive and graphical summaries, ? random variables and their distributions, ? interval estimation, ? hypothesis testing, ? relevant nonparametric methods, ? simple regression/correlation, and ? introduction to multiple regression. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [College-level algebra, health sciences grad student] or instr consent
PUBH 6451 - Biostatistics II
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
This course will cover more advanced aspects of statistical analysis methods with a focus on statistical modeling, including: ? two-way ANOVA, ? multiple linear regression, ? logistic regression, ? Poisson regression, ? log binomial and ordinal regression, ? survival analysis methods, including Kaplan-Meier analysis and proportional hazards (Cox) regression, ? power and sample size, and ? survey sampling and analysis. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [PubH 6450 with grade of at least B, health sciences grad student] or instr consent
PUBH 7405 - Biostatistical Inference I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
T-tests, confidence intervals, power, type I/II errors. Exploratory data analysis. Simple linear regression, regression in matrix notation, multiple regression, diagnostics. Ordinary least squares, violations, generalized least squares, nonlinear least squares regression. Introduction to General linear Model. SAS and S-Plus used. prereq: [[Stat 5101 or concurrent registration is required (or allowed) in Stat 5101], biostatistics major] or instr consent
PUBH 7406 - Biostatistical Inference II
Credits: 3.0 [max 4.0]
Typically offered: Every Spring
This course introduces students to a variety of concepts, tools, and techniques that are relevant to the rigorous design and analysis of complex biomedical studies. Topics include ANOVA, sample-size calculations, multiple testing, missing data, prediction, diagnostic testing, smoothing, variable selection, the bootstrap, and nonparametric tests. R software will be used. Biostatistics students are strongly encouraged to typeset their work using LaTeX or in R markdown. prereq: [7405, [STAT 5102 or concurrent registration is required (or allowed) in STAT 5102], biostatistics major] or instr consent
PUBH 7415 - Introduction to Clinical Trials
Credits: 3.0 [max 3.0]
Course Equivalencies: PubH 3415/PubH 7415
Typically offered: Every Fall & Summer
Hypotheses/endpoints, choice of intervention/control, ethical considerations, blinding/randomization, data collection/monitoring, sample size, analysis, writing. Protocol development, group discussions. prereq: 6414 or 6450 or one semester graduate-level introductory biostatistics or statistics or instr consent
PUBH 7430 - Statistical Methods for Correlated Data
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Correlated data arise in many situations, particularly when observations are made over time and space or on individuals who share certain underlying characteristics. This course covers techniques for exploring and describing correlated data, along with statistical methods for estimating population parameters (mostly means) from these data. The focus will be primarily on generalized linear models (both with and without random effects) for normally and non-normally distributed data. Wherever possible, techniques will be illustrated using real-world examples. Computing will be done using R and SAS. prereq: Regression at the level of PubH 6451 or PubH 7405 or Stat 5302. Familiarity with basic matrix notation and operations (multiplication, inverse, transpose). Working knowledge of SAS or R (PubH 6420).
STAT 5021 - Statistical Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Intensive introduction to statistical methods for graduate students needing statistics as a research technique. prereq: college algebra or instr consent; credit will not be granted if credit has been received for STAT 3011
STAT 5302 - Applied Regression Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications. prereq: 3032 or 3022 or 4102 or 5021 or 5102 or instr consent Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.
STAT 5303 - Designing Experiments
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Analysis of variance. Multiple comparisons. Variance-stabilizing transformations. Contrasts. Construction/analysis of complete/incomplete block designs. Fractional factorial designs. Confounding split plots. Response surface design. prereq: 3022 or 3032 or 3301 or 4102 or 5021 or 5102 or instr consent
STAT 5601 - Nonparametric Methods
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Order statistics. Classical rank-based procedures (e.g., Wilcoxon, Kruskal-Wallis). Goodness of fit. Topics may include smoothing, bootstrap, and generalized linear models. prereq: Stat classes 3032 or 3022 or 4102 or 5021 or 5102 or instr consent
KIN 5235 - Advanced Biomechanics II: Kinetics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
Kinetic aspects of human movement (single/multi-joint torques, simple inverted pendulum models, mass-spring systems). Analysis of experimental data and of computer simulations. Lectures, seminars, lab. prereq: [3112 or equiv], PMed 5135, undergrad college physics, intro calculus
KIN 5941 - Clinical Movement Neuroscience
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Periodic Spring
Various neural subsystems involved in controlling human motor function. How injury and disease of the nervous system affects motor behavior. Possibilities for rehabilitation and treatment. Lectures, seminars, class presentations. prereq: [3027 or ANAT 3001 or ANAT 3601 or ANAT 3611 or equiv], [PHSL 3051 or equiv], [4441]
KIN 8211 - Seminar: Perception and Action
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Survey of theory/research on use of perceptual information for control of action. Behavioral research on perceptual guidance of daily activities (e.g., standing, walking, driving). Perceptual control in context of expertise (e.g., sports). Perceptual-motor development. prereq: grad student or instr consent
KIN 8132 - Seminar: Motor Development
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Contemporary research literature on motor skill development from before birth to senescence. Emphasizes interaction between physical/environmental/performer constraints. Coordination/control of movement. prereq: grad student or instr consent
KIN 8135 - Seminar: Motor Control and Learning
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Advanced reading/discussion of research on motor control, motor learning, human performance. prereq: grad student or instr consent
RSC 5135 - Advanced Biomechanics I: Kinematics
Credits: 3.0 [max 3.0]
Course Equivalencies: RSc 5135/RSc 8135
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
How to describe/measure movement. Basic/applied biomechanics, pathokinesiology, and rehabilitation literature. Lecture, lab, seminar discussion. Meets with RSC 8135. prereq: instr consent
RSC 5841 - Applied Data Acquisition and Processing
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
This course will introduce students to collecting and processing biomedical time series data. Students will gain experience using data acquisition hardware common in many laboratories, as well as related software for acquisition of the data and digital signal processing. Data sources will include electromyography (EMG), wearable sensors, motion capture, and data from other systems based on the background and interests of students in the class. The overall goal of this course is to provide students with the necessary, fundamental skills to run a successful experiment, troubleshoot errors, and produce high quality data sets. prereq: prefer students to have completed general physics, introductory of short calculus
EPSY 8264 - Advanced Multiple Regression Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
General linear model used as context for regression. Matrix algebra, multiple regression, path analysis, polynomial regression, standardized regression, stepwise solutions, analysis of variance, weighted least squares, logistic regression. prereq: [8252 or equiv], regression/ANOVA course, familiarity with statistical analysis package
EPSY 8267 - Applied Multivariate Analysis
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Use/interpretation of results from several multivariate statistical techniques. Matrix algebra, variance/covariance, Hotelling's T2, GLM, MANOVA, MANCOVA, discriminant analysis, canonical correlations, dimensionality, principal components, latent composites, distance, hierarchical clustering. prereq: [8252 or equiv], familiarity with matrix algebra, knowledge of a computerized statistics package
EPSY 8282 - Statistical Analysis of Longitudinal Data
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Traditional/modern approaches to analyzing longitudinal data. Dependent t-test, repeated measures ANOVA/MANOVA. Linear mixed models, multilevel models, generalized models. prereq: [8252 or equiv]
PUBH 6450 - Biostatistics I
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
This course will cover the fundamental concepts of exploratory data analysis and statistical inference for univariate and bivariate data, including: ? study design and sampling methods, ? descriptive and graphical summaries, ? random variables and their distributions, ? interval estimation, ? hypothesis testing, ? relevant nonparametric methods, ? simple regression/correlation, and ? introduction to multiple regression. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [College-level algebra, health sciences grad student] or instr consent
PUBH 6451 - Biostatistics II
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
This course will cover more advanced aspects of statistical analysis methods with a focus on statistical modeling, including: ? two-way ANOVA, ? multiple linear regression, ? logistic regression, ? Poisson regression, ? log binomial and ordinal regression, ? survival analysis methods, including Kaplan-Meier analysis and proportional hazards (Cox) regression, ? power and sample size, and ? survey sampling and analysis. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [PubH 6450 with grade of at least B, health sciences grad student] or instr consent
PUBH 7405 - Biostatistical Inference I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
T-tests, confidence intervals, power, type I/II errors. Exploratory data analysis. Simple linear regression, regression in matrix notation, multiple regression, diagnostics. Ordinary least squares, violations, generalized least squares, nonlinear least squares regression. Introduction to General linear Model. SAS and S-Plus used. prereq: [[Stat 5101 or concurrent registration is required (or allowed) in Stat 5101], biostatistics major] or instr consent
PUBH 7406 - Biostatistical Inference II
Credits: 3.0 [max 4.0]
Typically offered: Every Spring
This course introduces students to a variety of concepts, tools, and techniques that are relevant to the rigorous design and analysis of complex biomedical studies. Topics include ANOVA, sample-size calculations, multiple testing, missing data, prediction, diagnostic testing, smoothing, variable selection, the bootstrap, and nonparametric tests. R software will be used. Biostatistics students are strongly encouraged to typeset their work using LaTeX or in R markdown. prereq: [7405, [STAT 5102 or concurrent registration is required (or allowed) in STAT 5102], biostatistics major] or instr consent
STAT 5201 - Sampling Methodology in Finite Populations
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Simple random, systematic, stratified, unequal probability sampling. Ratio, model based estimation. Single stage, multistage, adaptive cluster sampling. Spatial sampling. prereq: 3022 or 3032 or 3301 or 4102 or 5021 or 5102 or instr consent
STAT 5302 - Applied Regression Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications. prereq: 3032 or 3022 or 4102 or 5021 or 5102 or instr consent Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.
STAT 5303 - Designing Experiments
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Analysis of variance. Multiple comparisons. Variance-stabilizing transformations. Contrasts. Construction/analysis of complete/incomplete block designs. Fractional factorial designs. Confounding split plots. Response surface design. prereq: 3022 or 3032 or 3301 or 4102 or 5021 or 5102 or instr consent
STAT 5601 - Nonparametric Methods
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Order statistics. Classical rank-based procedures (e.g., Wilcoxon, Kruskal-Wallis). Goodness of fit. Topics may include smoothing, bootstrap, and generalized linear models. prereq: Stat classes 3032 or 3022 or 4102 or 5021 or 5102 or instr consent
KIN 5981 - Research Methodology in Kinesiology and Sport Management
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Defines/reviews various types of research in exercise/sport science, and physical education. Qualitative research, field studies, and methods of introspection as alternative research strategies to traditional scientific paradigm.
KIN 5987 - Professional Skills and Grant Writing for Health Sciences
Credits: 2.0 [max 2.0]
Grading Basis: OPT No Aud
Typically offered: Spring Odd Year
Introduction to structure/function of different organizations (e.g., NIH, AHA). Writing/reviewing grants/manuscripts. Preparing for a job in academia. prereq: Grad student
KIN 5123 - Motivational Interventions in Physical Activity
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring & Summer
This course prepares students to critically evaluate theory, motivational interventions, and psychological principles related to physical activity. Environmental and policy influences on physical activity behavior and intervention components, design, and evaluation will be discussed. The influence of physical activity on mental health, self-perceptions, stress, anxiety, depression, emotional well-being, cognitive function, and health-related quality of life will be reviewed. This course will help students to better understand and modify exercise behavior and review the most commonly studied psychosocial influences and consequences of physical activity. This class integrates theoretical principles and the latest research with intervention strategies that students can apply in real-world settings.
KIN 5126 - Social Psychology of Sport & Physical Activity
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Theory/research on social influences, individual differences, motivational processes. How sport/physical activity contribute to psycho-social development. Social psychological factors influencing physical activity beliefs/behaviors. prereq: 3126W or equiv or grad student or instr consent
KIN 5136 - Psychology of Coaching
Credits: 3.0 [max 3.0]
Typically offered: Every Fall, Spring & Summer
Psychological dimensions of coaching across age levels, including coaching philosophy, leadership, communication skills, motivation, and mental skills training for performance enhancement.
KIN 5371 - Sport and Society
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 5371/Rec 5371
Grading Basis: A-F or Aud
Typically offered: Every Spring
Sport, sporting processes, social influences, systems. Structures that have effected and exist within/among societies, nations, and cultures. Contemporary issues such as social differentiation, violence, and honesty. prereq: [3126W, grad student] or instr consent
KIN 5720 - Special Topics in Kinesiology
Credits: 2.0 -4.0 [max 12.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Current issues in the broad field and subfields in kinesiology, or related coursework in areas not normally available through regular offerings.
KIN 5511 - Sport and Gender
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 5511/Rec 5511
Grading Basis: A-F only
Typically offered: Every Fall
Critically examines women's involvement in/contributions to sport, physical activity, and leisure.
KIN 5723 - Psychology of Sport Injury and Rehabilitation
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Psychosocial bases of risk factors preceding sport injury, responses to the occurrence of sport injury, and the rehabilitation process. Lecture, discussion, guest lecture, interviews, and presentation experience. prereq: Intro psych course
KIN 8126 - Sports Medicine Psychology
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Periodic Spring
Advanced seminar course. Multidisciplinary contributors to sports medicine psychology. Theory, research, and practice in the behavioral/social aspects of injury prevention/experiences among physically active populations across the life span. prereq: Grad student or instr consent
KIN 8136 - Developmental Sport and Exercise Psychology
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Sport and exercise psychology from a life span developmental perspective. Theoretical perspectives, self-perceptions, social influences, emotional development, motivational processes, self-regulation, development of expertise, moral development, sport injury, and gender and cultural diversity. prereq: Grad student or instr consent
KIN 5981 - Research Methodology in Kinesiology and Sport Management
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Defines/reviews various types of research in exercise/sport science, and physical education. Qualitative research, field studies, and methods of introspection as alternative research strategies to traditional scientific paradigm.
EPSY 5247 - Qualitative Methods in Educational Psychology
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Introduction to qualitative methods of inquiry. Contrasting different research traditions (e.g., case study, phenomenology, ethnography, social interactionism, critical theory). Practice with field notes, observations, and interviewing. Use of NVIVO to track/code data. prereq: Graduate student or Applied Psychology in Educational and Community Settings Minor
EPSY 8264 - Advanced Multiple Regression Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
General linear model used as context for regression. Matrix algebra, multiple regression, path analysis, polynomial regression, standardized regression, stepwise solutions, analysis of variance, weighted least squares, logistic regression. prereq: [8252 or equiv], regression/ANOVA course, familiarity with statistical analysis package
EPSY 8266 - Statistical Analysis Using Structural Equation Methods
Credits: 3.0 [max 3.0]
Prerequisites: 8265, [8252 or equiv]
Typically offered: Periodic Spring
Quantitative techniques using manifest/latent variable approaches for analysis of educational/social science data. Introduction to structural equation modeling approaches to multiple regression, factor analysis, path modeling. Developing, estimating, interpreting structural equation models. prereq: 8265, [8252 or equiv]
EPSY 8267 - Applied Multivariate Analysis
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Use/interpretation of results from several multivariate statistical techniques. Matrix algebra, variance/covariance, Hotelling's T2, GLM, MANOVA, MANCOVA, discriminant analysis, canonical correlations, dimensionality, principal components, latent composites, distance, hierarchical clustering. prereq: [8252 or equiv], familiarity with matrix algebra, knowledge of a computerized statistics package
EPSY 8282 - Statistical Analysis of Longitudinal Data
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Traditional/modern approaches to analyzing longitudinal data. Dependent t-test, repeated measures ANOVA/MANOVA. Linear mixed models, multilevel models, generalized models. prereq: [8252 or equiv]
PSY 8209 - Research Methods in Social Psychology
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Fall Odd Year
Experimental/quasi-experimental methods for research in social psychology. Statistical, interpretive, operational, and ethical issues. prereq: Psych PhD student
PUBH 6810 - Survey Research Methods
Credits: 3.0 [max 3.0]
Grading Basis: OPT No Aud
Typically offered: Every Spring
Theory/application of survey research in data collection. Sampling, item development, instrument design/administration to conduct survey or be aware of issues related to design/implementation. Identification of sources of error in survey research.
PUBH 7401 - Fundamentals of Biostatistical Inference
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Part of two-course sequence intended for PhD students in School of Public Health who need rigorous approach to probability/statistics/statistical inference with applications to research in public health. prereq: Background in calculus; intended for PhD students in public hlth and other hlth sci who need rigorous approach to probability/statistics and statistical inference with applications to research in public hlth
PUBH 7405 - Biostatistical Inference I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
T-tests, confidence intervals, power, type I/II errors. Exploratory data analysis. Simple linear regression, regression in matrix notation, multiple regression, diagnostics. Ordinary least squares, violations, generalized least squares, nonlinear least squares regression. Introduction to General linear Model. SAS and S-Plus used. prereq: [[Stat 5101 or concurrent registration is required (or allowed) in Stat 5101], biostatistics major] or instr consent
PUBH 7406 - Biostatistical Inference II
Credits: 3.0 [max 4.0]
Typically offered: Every Spring
This course introduces students to a variety of concepts, tools, and techniques that are relevant to the rigorous design and analysis of complex biomedical studies. Topics include ANOVA, sample-size calculations, multiple testing, missing data, prediction, diagnostic testing, smoothing, variable selection, the bootstrap, and nonparametric tests. R software will be used. Biostatistics students are strongly encouraged to typeset their work using LaTeX or in R markdown. prereq: [7405, [STAT 5102 or concurrent registration is required (or allowed) in STAT 5102], biostatistics major] or instr consent
KIN 5725 - Organization and Management of Physical Education and Sport
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring & Summer
Comprehensive analysis of organization and management of physical education and sport in educational settings. Focus on management and planning processes, management skills, functions, roles, decision making, leadership, shared systems, and organizational motivation. For physical education teachers, coaches, community sport administrators. prereq: Grad/initial licensure or instr consent
KIN 5801 - Legal Aspects of Sport and Physical Activity
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Legal issues related to sport and physical activity settings and facilities in public/private sectors
KIN 8980 - Graduate Research Seminar in Kinesiology
Credits: 3.0 [max 9.0]
Grading Basis: A-F only
Typically offered: Every Fall
Reporting/discussion of student/faculty research activity. prereq: KIN M.S. or Ph.D. or SMGT M.A. or instr consent
KIN 8128 - Doctoral Sport Management Seminar
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 8128/Rec 8128
Grading Basis: A-F only
Typically offered: Periodic Fall & Spring
Analysis of current literature, theoretical constructs, research methodology and design relative to sport management. Focuses on student-selected topics, research problems. prereq: PhD student, instr consent
KIN 5111 - Sports Facilities
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Steps in planning/building facilities for athletics, physical education, and sport for college, professional, and public use. prereq: Kin or Rec grad student or MEd student
KIN 5511 - Sport and Gender
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 5511/Rec 5511
Grading Basis: A-F only
Typically offered: Every Fall
Critically examines women's involvement in/contributions to sport, physical activity, and leisure.
KIN 5371 - Sport and Society
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 5371/Rec 5371
Grading Basis: A-F or Aud
Typically offered: Every Spring
Sport, sporting processes, social influences, systems. Structures that have effected and exist within/among societies, nations, and cultures. Contemporary issues such as social differentiation, violence, and honesty. prereq: [3126W, grad student] or instr consent
KIN 5421 - Sport Finance
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Summer
Introduction to financial analysis in sport. Cash flow statements, budgeting issues, traditional/innovative revenue producing strategies available to sport organizations. Discussion, practical analysis of current market. prereq: Grad student or instr consent
KIN 5461 - Issues in the Sport Industry
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Critical analysis of management issues within sport industry. Strategic management, corporate social responsibility, human resource management/diversity, governance, sport globalization, sport development. prereq: postbac or grad student or instr consent
KIN 5601 - Sport Management Ethics and Policy
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 5601/Rec 5601
Grading Basis: A-F or Aud
Typically offered: Every Spring
How to critically analyze ethical concepts that underpin or inform sport policies and evaluate sport policies from a normative point of view. Selected sport policy issues are used to illustrate relevance of ethical considerations in policy development and to explore the ethical implications of sport policy. prereq: MEd or grad student or instr consent
KIN 5631 - Programming and Promotion in Sport
Credits: 3.0 [max 3.0]
Course Equivalencies: Kin 5631/Rec 5631
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to marketing concepts as they apply to sport industry. Consumer behavior, market research, marketing mix, corporate sponsorship, licensing. Discussion, practical application. prereq: Kin or Rec grad student or instr consent
KIN 5725 - Organization and Management of Physical Education and Sport
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring & Summer
Comprehensive analysis of organization and management of physical education and sport in educational settings. Focus on management and planning processes, management skills, functions, roles, decision making, leadership, shared systems, and organizational motivation. For physical education teachers, coaches, community sport administrators. prereq: Grad/initial licensure or instr consent
KIN 5801 - Legal Aspects of Sport and Physical Activity
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Legal issues related to sport and physical activity settings and facilities in public/private sectors
KIN 5981 - Research Methodology in Kinesiology and Sport Management
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Defines/reviews various types of research in exercise/sport science, and physical education. Qualitative research, field studies, and methods of introspection as alternative research strategies to traditional scientific paradigm.
OLPD 5056 - Case Studies for Policy Research
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall, Spring & Summer
This course introduces students to knowledge and skills appropriate for the conduct of rigorous case study research in educational, organizational, and other social settings. Underlying purposes and assumptions of case study methods will be examined as well as a variety of methodological approaches. The course focuses on the use of qualitative and mixed-methods approaches as these are the predominant strategies employed in contemporary case study research. Accordingly, it emphasizes links between research purposes, the conceptualization of case study projects, and the development of researchable questions. It also takes up a variety of ethical and political issues related to working with participants during the research process, as well as contemporary trustworthiness criteria for case study reports. The bulk of the course is given to training in observation, generating field notes, interviewing, collecting material cultural artifacts, using surveys, and analyzing, interpreting, and writing up case study data. The first segment of the course focuses on a critical discussion of research paradigms and epistemological assumptions of a variety of case study approaches. Students choose and critique a published case study from their field of interest. The second part of the course is devoted to a very small scale case study project which students design and carry out themselves. This project is supported by relevant readings and in-class activities (including peer review) related to the actual conduct of case study research.
OLPD 5061 - Ethnographic Research Methods
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall, Spring & Summer
This course introduces students to knowledge and skills appropriate for the conduct of ethnographic research. Underlying purposes, assumptions, and distinctive characteristics of ethnographic methods will be examined as well as appropriate exemplars. Accordingly, the course emphasizes links between research purposes, the conceptualization of ethnographic projects and the development of researchable questions. The course also takes up a variety of ethical and political issues related to working with participants during the research process, as well as contemporary trustworthiness criteria for ethnographic written accounts. The bulk of the course is given to training in observation, generating field notes, developing interview questions, interviewing, collecting material cultural artifacts, using surveys, and analyzing, interpreting, and writing up ethnographic data. The first part of the course focuses on a critical discussion of ethnographic research purposes, epistemological assumptions, and essential features. Students choose and explore a published ethnographic study from their field of interest. The second part of the course is devoted to a very small scale ethnographic project which students design and carry out themselves. This project is supported by relevant readings and in-class activities (including peer review) related to the actual conduct of ethnographic research.
EPSY 5247 - Qualitative Methods in Educational Psychology
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Introduction to qualitative methods of inquiry. Contrasting different research traditions (e.g., case study, phenomenology, ethnography, social interactionism, critical theory). Practice with field notes, observations, and interviewing. Use of NVIVO to track/code data. prereq: Graduate student or Applied Psychology in Educational and Community Settings Minor
EPSY 8264 - Advanced Multiple Regression Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
General linear model used as context for regression. Matrix algebra, multiple regression, path analysis, polynomial regression, standardized regression, stepwise solutions, analysis of variance, weighted least squares, logistic regression. prereq: [8252 or equiv], regression/ANOVA course, familiarity with statistical analysis package
EPSY 8265 - Factor Analysis
Credits: 3.0 [max 3.0]
Prerequisites: [8252 or equiv or #]
Typically offered: Every Fall
Factor analytic techniques/applications. Component, common factor, confirmatory analysis. Factor extraction, estimating number of dimensions. Rotation, factor scores, hierarchical factor analysis. prereq: [8252 or equiv or instr consent]
EPSY 8266 - Statistical Analysis Using Structural Equation Methods
Credits: 3.0 [max 3.0]
Prerequisites: 8265, [8252 or equiv]
Typically offered: Periodic Spring
Quantitative techniques using manifest/latent variable approaches for analysis of educational/social science data. Introduction to structural equation modeling approaches to multiple regression, factor analysis, path modeling. Developing, estimating, interpreting structural equation models. prereq: 8265, [8252 or equiv]
EPSY 8267 - Applied Multivariate Analysis
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Use/interpretation of results from several multivariate statistical techniques. Matrix algebra, variance/covariance, Hotelling's T2, GLM, MANOVA, MANCOVA, discriminant analysis, canonical correlations, dimensionality, principal components, latent composites, distance, hierarchical clustering. prereq: [8252 or equiv], familiarity with matrix algebra, knowledge of a computerized statistics package
FSOS 8013 - Qualitative Family Research Methods
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Approaches to qualitative family research evaluation. Phenomenological, feminist, grounded theory, content analytic, ethnomethodological, ethnographic, program evaluation. Theory, research examples, student projects.