Stationary series, spectral analysis, models in time series: autoregressive, moving average, ARMA and ARIMA. Smoothing series, computational techniques and computer packages for time series. Prerequisites: STAT 372 and 378. Note: This course may only be offered in alternate years.

This course is designed to give credit to mature and able students for reading in areas not covered by courses, under the supervision of a staff member. A student, or group of students, wishing to use this course should find a staff member willing to supervise the proposed reading program. A detailed description of the material to be covered should be submitted to the Chair of the Department Honors Committee. (This should include a description of testing methods to be used.) The program will require the approval of both the Honors Committee, and the Chair of the Department. The students' mastery of the material of the course will be tested by a written or oral examination. This course may be taken in Fall or Winter and may be taken any number of times, subject always to the approval mentioned above. Prerequisite: Any 300-level STAT course.

This topics course is designed for new course offerings that may be offered in a given term. Prerequisites: One of STAT 266 or 276. Additional prerequisites may be required. Note: Credit for this course may be obtained more than once.

This course provides students in Major, Specialization and Honors programs an opportunity to pursue research in statistics under the direction of a member of the Department. Course requirements include at least one oral presentation and a written final report. Students interested in taking this course should contact the course coordinator two months in advance. Credit for this course may be obtained more than once. Prerequisites: a 300-level STAT course and consent of the course coordinator.

Basic principles of experimental design, completely randomized design-one way ANOVA and ANCOVA. Randomized block design. Latin square design, Multiple comparisons. Nested designs. Factorial experiments. Each student will give a written report and seminar presentation highlighting statistical methods used in a research project. Prerequisites: STAT 252 or 337 or equivalent and a course in linear algebra. Note: Cannot be used for credit towards a graduate program in Statistics.

Simple linear regression analysis, inference on regression parameters, residual analysis, prediction intervals, weighted least squares. Multiple regression analysis, inference about regression parameters, multicollinearity and its effects, indicator variables, selection of independent variables. Non-linear regression. Each student will give a written report and seminar presentation highlighting statistical methods used in a research project. Prerequisite: STAT 337 or equivalent and a course in linear algebra. Note: Cannot be used for credit towards a graduate program in Statistics.

Theory and applications of time series modelling, stationarity, autocorrelation. Spectral properties, filtering. Box-Jenkins models, seasonality. Each student will give a written report and seminar presentation highlighting statistical methods used in a research project. Prerequisite: STAT 372 and 378 or consent of Instructor.

Basic sampling schemes for finite populations: simple random sampling, stratified random sampling, systematic sampling and cluster sampling. Unequal probability sampling. Ratio and regression estimators. Prerequisite: A course in Statistical Inference at the 300 level or permission from the instructor. Note: Cannot be used for credit towards a graduate program in Statistics.

Principles of statistical model building and analysis applied in linear and generalized linear models and illustrated through multivariate methods such as repeated measures, principal components, and supervised and unsupervised classification. Each student will give a written report and seminar presentation highlighting statistical methods used in a research project. Prerequisites: STAT 501, 502 or equivalent. Note: Cannot be used for credit towards a thesis-based graduate program in Statistics.

Introduction to mathematical techniques commonly used in theoretical Statistics, with applications. Applications of diagonalization results for real symmetric matrices, and of continuity, differentiation, Riemann-Stieltjes integration and multivariable calculus to the theory of Statistics including least squares estimation, generating functions, distribution theory. Prerequisite: consent of Department.

Introduction to contemporary computational culture: reproducible coding, literate programming. Monte Carlo methods: random number generation, variance reduction, numerical integration, statistical simulations. Optimization (linear search, gradient descent, Newton-Raphson, method of scoring, and their specifics in the statistical context), EM algorithm. Fundamentals of convex optimization with constraints. Prerequisites: consent of the instructor.

This course is designed to equip students with essential statistical knowledge and skills necessary for the successful clinical trial design and analysis. This course covers a wide range of statistical topics specific to clinical trials, including intention-to-treat versus efficacy trials, principles of sampling and exclusion, methods of allocation and techniques of randomization, parallel versus cross over design, cluster randomization designs, statistical analysis planning, external and internal validation, and reports of statistical findings. Additionally, the course will explore other selected topics related to logistical issues in the management of clinical trials. Prerequisite: consent of the instructor. Notes: Students outside of the course-based MSc with a specialization in Biostatistics need permission from the Department to enroll in this course. Thesis-based graduate students in Mathematical and Statistical Sciences cannot take this course for credit.

This course is a continuation of Statistics for Clinical Trials I, with a focus on statistical computation and data analysis techniques specifically tailored for clinical trials. Students will work with the R and SAS statistical programming languages to gain a comprehensive understanding of these methods in the clinical trials context. The primary goal is to equip graduate students with the statistical skills required for data analysis in clinical trials. Successful students will become proficient in using statistical computational tools to analyze real-world clinical datasets and will be exposed to advanced statistical techniques and best practices for data storage, management, and analysis. Key statistical topics covered in this course include sampling designs, chi-square tests, linear models, mixed-effects models for repeated measurements and survival analysis. Prerequisite: STAT 514. Notes: Students outside of the course-based MSc with a specialization in Biostatistics need permission from the Department to enroll in this course. Thesis-based graduate students in Mathematical and Statistical Sciences cannot take this course for credit.

Survival and hazard functions, censoring, truncation. Non-parametric, parametric and semi-parametric approaches to survival analysis including Kaplan-Meier estimation and Cox's proportional hazards model. Prerequisite: STAT 372 or consent of Department.

Review of basic statistical concepts of inference and probability theory. Includes applied methods of Linear and non-linear regression and analysis of variance for designed experiments, multiple comparisons, correlations, modeling and variable selection, multicollinearity, predictions, confounding and Simpson's paradox. Includes case studies and real data applications. Each researcher works on a project to present, highlighting the methods used in the project. Prerequisite: STAT 437 equivalent or consent of the instructor.

The course focuses on statistical learning techniques, in particular those of supervised classification, both from statistical (logistic regression, discriminant analysis, nearest neighbours, and others) and machine learning background (tree-based methods, neural networks, support vector machines), with the emphasis on decision-theoretic underpinnings and other statistical aspects, flexible model building (regularization with penalties), and algorithmic solutions. Selected methods of unsupervised classification (clustering) and some related regression methods are covered as well. Prerequisite: Consent of the instructor.

Classical ruin theory, individual risk models, collective risk models, models for loss severity: parametric models, tail behavior, models for loss frequency, mixed Poisson models; compound Poisson models, convolutions and recursive methods, probability and moment generating functions. Prerequisite: STAT 371 or equivalent. Note: Cannot be used for credit towards a thesis-based graduate program in the Department of Mathematical and Statistical Sciences.

Review of basic sampling schemes: simple random sampling, and stratified random sampling, and systematic sampling. Multistage sampling schemes. Estimation of nonlinear parameters: ratios, regression coefficients, and correlation coefficients. Variance estimation techniques: linearization, BRR, jackknife, and bootstrap. Selected topics: model-based estimation, regression analysis from complex survey data. Relevant computer packages. Prerequisites: STAT 361, 372, 471.

Sampling models and methods of inference for discrete data. Maximum likelihood estimation for complete contingency tables, measures of association and agreement. Goodness-of-fit. Incomplete tables. Analysis of square tables; symmetry and marginal homogeneity. Model selection and closeness of fit; practical aspects. Chi-square tests for categorical data from complex surveys. Prerequisite: STAT 372 or 471.

An introduction to the theory of statistical inference. Topics to include exponential families and general linear models, likelihood, sufficiency, ancillarity, interval and point estimation, asymptotic approximations. Optional topics as time allows, may include Bayesian methods, Robustness, resampling techniques. This course is intended primarily for MSc students. Prerequisite: STAT 471 or consent of Department.

The general linear model. Fully randomized designs, one-way layout, multiple comparisons. Block designs, Latin squares. Factorial designs confounding, fractions. Nested designs, randomization restrictions. Response surface methodology. Analysis of covariance. Prerequisite: STAT 368 and a 400-level STAT course.

Measure and integration, Laws of Large Numbers, convergence of probability measures. Conditional expectation as time permits. Prerequisites: STAT 471 and STAT 512 or their equivalents.

The multivariate normal distribution, multivariate regression and analysis of variance, classification, canonical correlation, principal components, factor analysis. Prerequisite: STAT 372 and STAT 512.

Multiple linear regression, ordinary and generalized least squares, partial and multiple correlation. Regression diagnostics, collinearity, model building. Nonlinear regression. Selected topics: robust and nonparametric regression, measurement error models. Prerequisites: STAT 378 and a 400-level statistics course.

Elements of stochastic processes. Discrete and continuous time Markov Chains; Birth and Death processes. Branching processes. Brownian Motion. General Stationary and Markov processes. Examples. Prerequisite: STAT 471 or consent of Instructor.

Data analysis, problem solving, oral communication with clients, issues in planning experiments and collecting data; practical aspects of consulting and report writing. Corequisite: STAT 568 and 578 or their equivalents.

Students will be supervised by an individual staff member to participate in areas of research interest of that staff member. Students can register only with the permission of the Chair of the Department in special circumstances. Will not be counted toward the minimum course requirement for graduate credits.

Advanced statistical design and methods. Topics include sampling, multivariate techniques, survival analysis, power and sample size, linear and non linear regression, longitudinal and repeated measures data, and analysis of seasonal or time series data. Topics to be covered can be influenced by the registered researchers. Includes critical review and case studies with real data applications. Each researcher works on a project to present, highlighting the methods used in the project. Prerequisite: STAT 537 or equivalent or consent of the instructor. Cannot be used for credit towards a graduate program in Statistics.

Modern methods of statistical inference. Various versions of likelihood: conditional, marginal, integrated, profile, partial, empirical. Estimating equations. Semi-parametric models. Foundational issues. Prerequisites: STAT 512 and 566.

Approximation techniques and asymptotic methods in statistics. Topics may include second and higher order expansions, asymptotics of likelihood based estimation and testing. Edgeworth expansions, exponential tilting, asymptotic relative efficiency, U-, M-, L-, and R-estimation. Prerequisites: STAT 566 or 664 and 512 or the equivalent.

Open only to students taking the MSc non-thesis option in statistics.

Open only to students taking the MSc non-thesis option in statistics.

Open only to students taking the MSc non-thesis option in statistics.

Open only to students taking the MSc non-thesis option in Statistics.

Open only to students taking the MSc non-thesis option in Statistics.

Students will work on statistical clinical programming tasks through paid internships. These internships may be provided by an external company in partnership with the University of Alberta. Prerequisite: STAT 515. Notes: Enrolment in this course needs permission from the Department. Only students in the course-based MSc with a specialization in Biostatistics can get credit for this course. This course can be taken more than once for credit with approval by the Department.

Collecte de données et leur présentation, statistiques descriptives. Loi de probabilité, distribution d'échantillonnage et théorème limite central, estimation ponctuelle et tests d'hypothèses. Corrélation et régression linéaire simple. Mesure d'ajustement et tableaux de contingences. Préalable: Mathématiques 30-1 ou 30-2. Note: Ce cours n'est pas accessible aux étudiants ayant ou postulant des crédits pour un cours de STAT, KIN 109, PEDS 109, PSYCH 211, SCSOC 322, SOC 210, ou SCI 151.

An examination of the interrelations of science, technology, society and environment, emphasizing an interdisciplinary humanities and social sciences perspective. Note: not to be taken by students with credit in INT D 200.

An examination of the interrelations between human cultural frameworks and environmental issues, emphasizing an interdisciplinary humanities and social sciences perspective.

An individual research project on issues at the intersection of Science, Technology, and Society, to be completed under the direction of a supervisor. Prerequisite: consent of the Program Director.

Lecture series on research techniques in the biomedical sciences intended for students with an advanced medical background. Prerequisite: consent of Department

Lecture series on research techniques in the biomedical sciences intended for students with an advanced medical background. Prerequisite: consent of Department

Reading and study of topics in biomedical research of relevance to the student's interest under direction of one or more faculty members.

Student internship for students registered in the MD program.

The course reviews the fundamentals of microvascular surgery, and then allows supervised instruction in techniques including dissection, vascular anastomosis, mobilization of free flaps of vascularized tissue, transplantation and vein grafts. This course is intended for individuals with an extensive background in the theory and practice of surgery such as Surgery Residents and experienced researchers in the field. Prerequisite: consent of Department.

Student internship for students registered in the MD Program.

A weekly series of seminars on current research is held during Fall and Winter Terms. Graduate students must attend and make two presentations in this series.

A weekly series of seminars on current research is held during Fall and Winter Terms. Graduate students must attend and make two presentations in this series.

An introduction to the history of sustainability as a concept, contemporary sustainability issues, and the diverse perspectives that disciplines and professions take on while approaching sustainability. Not available to students with credit in HGP 250 or HGEO 250.

An introduction to sustainable development with a global perspective and a focus on the United Nations Sustainable Development Goals (SDGs).

Topics vary; may be taken more than once for credit provided no topic is repeated.

Topics vary; may be taken more than once for credit provided no topic is repeated.

Topics vary; may be taken more than once for credit provided no topic is repeated.

Directed research or study in an area of sustainability defined by the student and a supervising instructor. May be used to fill the integrative project requirement of the Certificate in Sustainability. Registration requires approval of the Sustainability Council Office.

Directed research or study in an area of sustainability defined by the student and a supervising instructor. May be used to fill the integrative project requirement of the Certificate in Sustainability. Registration requires approval of the Sustainability Council Office.

Directed research or study in an area of sustainability defined by the student and a supervising instructor. May be used to fill the integrative project requirement of the Certificate in Sustainability. Registration requires approval of the Sustainability Council Office.

This course provides an interdisciplinary introduction to theoretical and applied foundations of sustainability. It introduces concepts of systems thinking, interdisciplinarity and sustainable development. It explores the root causes of environmental and social sustainability and diverse approaches to achieving sustainable solutions.

This course equips students with practical skills to apply sustainability principles across various sectors, incorporating tools for impact assessment and case studies, including Indigenous approaches to contemporary challenges. Students will develop practical problem-solving abilities and gain the capacity to implement culturally inclusive and contextually relevant sustainable solutions.

This course prepares students to lead and manage sustainability transitions by exploring strategies like policy development, organizational change, and community-driven initiatives, with a focus on ethical leadership, stakeholder engagement, and culturally informed practices. Students will gain insights into culturally informed leadership and its crucial role in achieving successful sustainability transitions.

Intended for students with no previous knowledge of the language and designed to develop basic skills: listening, reading, speaking, writing, and intercultural competence. Note: not to be taken by students with native or near native proficiency, or with Swedish 30 or its equivalents in Canada and other countries.

Prerequisite: SWED 111 or consent of Department. Note: not to be taken by students with native or near native proficiency, or with Swedish 30 or its equivalents in Canada and other countries.

Intended to expand comprehension and production skills in written and oral Swedish with a focus on intercultural competence. Prerequisite: Swedish 30 (or equivalent) or SWED 112 or consent of Department.

Prerequisite: SWED 211 or consent of Department.

Production techniques and associated safe working practices. Note: Restricted to BFA in Drama (Production) students.

Studies in drafting and perspective drawing for the stage. Note: Restricted to BFA in Drama (Production) students.

Study and practice of the studio techniques employed in theatre design. Normally restricted to BFA in Drama (Production) students. Prerequisite: consent of Department.

Study and practice of design for the theatre. Note: Restricted to BFA in Drama (Production): Design students or consent of department.

Study and practice of design for the theatre. Note: Restricted to BFA in Drama (Production): Design students or consent of department.

Study in practice of computer graphic techniques employed in theatre design. Note: Restricted to BFA in Drama (Production): Design and Technical Production students or consent of department.

Computer aided design for the theatre designer and technician. Note: Restricted to BFA in Drama (Production): Design and Technical Production students.

Theory and techniques of the texturing and painting of scenery. Note: Restricted to BFA in Drama (Production) students, or consent of department.

A survey of style in western civilization from the ancients to the Renaissance. Prerequisite: consent of department. Note: Not to be taken by students with credit in HECOL 150, 268 or 360.

Development and application of drawing techniques with emphasis on drawing for the theatre. Note: A single-term course offered over two terms. Note: Restricted to BFA in Drama (Production): Design students.

Development and application of drawing techniques with emphasis on drawing for the theatre. Note: A single-term course offered over two terms. Note: Restricted to BFA in Drama (Production): Design students.

Further study and practice of design for the theatre. Prerequisite: T DES 270. Note: Restricted to BFA in Drama (Production): Design students.

Further study and practice of design for the theatre. Prerequisite: T DES 270. Note: Restricted to BFA in Drama (Production): Design students.

Exploration, practice and experimentation with 3D CAD for theatrical application. Note: Restricted to BFA in Drama (Production): Design and Technical Production students. Offered in alternate years.

Theory and techniques of lighting design. Note: Restricted to BFA in Drama (Production) students, or consent of department.

Prerequisite: T DES 373. Note: Restricted to BFA in Drama (Production): Design students, or consent of department.

A survey of style in western civilization from the Renaissance to the present. Prerequisite: consent of department. Note: Not to be taken by students with credit in HECOL 150, 268 or 360.

Practical experience in assisting the designer. Corequisite: T DES 370. Note: A single-term course offered over two terms. Restricted to BFA in Drama (Production): Design students.

Practical experience in assisting the designer. Corequisite: T DES 370. Note: A single-term course offered over two terms. Restricted to BFA in Drama (Production): Design students.

Further development and application of drawing techniques with emphasis on drawing for the theatre. Note: A single-term course offered over two terms. Note: Restricted to BFA in Drama (Production): Design students. Offered in alternate years.

Further development and application of drawing techniques with emphasis on drawing for the theatre. Note: A single-term course offered over two terms. Note: Restricted to BFA in Drama (Production): Design students. Offered in alternate years.

A specialized course for advanced students, designed to meet the needs of the individual. Prerequisite: T DES 370. Note: Restricted to BFA in Drama (Production): Design students.

A specialized course for advanced students, designed to meet the needs of the individual. Prerequisite: T DES 370. Note: Restricted to BFA in Drama (Production): Design students.

Portfolio assessment.

Portfolio assessment.

Theory and techniques of stage costuming. Note: Restricted to BFA in Drama (Production) students, or consent of department.

Prerequisite: T DES 473. Note: Restricted to BFA in Drama (Production): Design students or consent of department.

History of design and scenography for the theatre. Offered in alternate years.

Practical experience in designing an element or elements of a production. Note: Restricted to BFA in Drama (Production): Design students.

Practical experience in designing an element or elements of a production. Note: Restricted to BFA in Drama (Production): Design students.

Practical experience in assistant designing or design. May be taken in conjunction with either T Des 370 or T Des 477. Note: Restricted to students in the Design route of the BFA in Drama (Production).

Practical experience in assistant designing or design. May be taken in conjunction with either T Des 370 or T Des 477. Note: Restricted to students in the Design route of the BFA in Drama (Production).