COLLEGE OF SCIENCE. John D. Hromi Center for Quality and Applied Statistics. NEW (or REVISED) COURSE: COS-STAT-701 Foundations of Experimental Design

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1 ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE John D. Hromi Center for Quality and Applied Statistics NEW (or REVISED) COURSE: COS-STAT-701 Foundations of Experimental Design 1.0 Course Designations and Approvals Required course approvals: Academic Unit Curriculum Committee College Curriculum Committee Optional designations: Is designation desired? General Education: Yes No Writing Intensive: Yes No Honors Yes No Approval request date: *Approval request date: Approval granted date: **Approval granted date: 2.0 Course information: Course title: Foundations of Experimental Design Credit hours: 3 Prerequisite(s): One semester course in basic statistics Co-requisite(s): None Course proposed by: Joseph G. Voelkel Effective date: August 2013 Contact hours Maximum students/section Classroom 3 25 Lab 0 Studio 0 Other (specify) 0 2.a Course Conversion Designation*** (Please check which applies to this course). *For more information on Course Conversion Designations please see page four. Semester Equivalent (SE) Please indicate which quarter course it is equivalent to: Semester Replacement (SR) Please indicate the quarter course(s) this course is replacing: Design of Experiments I Design of Experiments III (partial) New July 27, 2010

2 2.b Semester(s) offered (check) Fall (distance) Spring (campus) Summer Other All courses must be offered at least once every 2 years. If course will be offered on a bi-annual basis, please indicate here: 2.c Student Requirements Students required to take this course: (by program and year, as appropriate) Students in MS in Applied Statistics program Students in Advanced Certificate programs in CQAS Students who might elect to take the course: Graduate students in other programs interested in experimental design. In the sections that follow, please use sub-numbering as appropriate (eg. 3.1, 3.2, etc.) 3.0 Goals of the course (including rationale for the course, when appropriate): 3.1 To introduce students to the importance of sound statistical techniques in the design and analysis of experiments 3.2 To provide students with the appropriate tools and techniques to design, implement, and analyze a broad class of experimental designs. 4.0 Course description (as it will appear in the RIT Catalog, including pre- and corequisites, and quarters offered). Please use the following format: COS-STAT-701 Foundations of Experimental Design This course is an introduction to experimental design with emphases on both foundational and practical aspects. Topics include the role of statistics in scientific experimentation, completely randomized designs, randomized complete block designs, nested designs, Latin square designs, incomplete block designs, general factorial designs, split-plot designs, random vs. fixed effects, and mixed models. 5.0 Possible resources (texts, references, computer packages, etc.) Required: 5.1 Design and Analysis of Experiments, A. Dean and D. Voss, Springer, NY 5.2 Statistical software for the design and analysis of experiments, such as Minitab 2

3 6.0 Topics (outline): 6.1 Introduction to Experimental Designs 6.2 Experiments with One Factor at Two Levels 6.3 Extended Structure Diagrams 6.4 One-Factor Fixed-Effects Completely Randomized Designs 6.5 One-Factor Random-Effects Model 6.6 Checking Model Assumptions 6.7 Contrasts 6.8 Multiple Comparisons 6.9 Factorial Designs 6.10 Covariates in Experimental Designs and Analysis 6.11 Blocking: Randomized Complete Blocks 6.12 Nested Designs 6.13 Other Block Designs 6.14 General Complete Balanced Designs 6.15 Analysis of General Complete Balanced Designs 6.16 Additional Topics on Complete, Balanced, Designs 6.17 Other Experimental Designs 7.0 Intended course learning outcomes and associated assessment methods of those outcomes (please include as many Course Learning Outcomes as appropriate, one outcome and assessment method per row). Course Objectives Level 1: Knowledge: 1.1.Defines randomized, controlled, double-blind, blocks, factorial design Level 2: Comprehension: 2.1.Gives examples of point estimation, interval construction, and hypothesis testing 2.2.Describes the types of multiple comparison procedures 2.3.Gives examples of named designs: RCBD, splitplot, strip-plot Level 3: Application: 3.1.Constructs an ANOVA model from an Extended Structure Diagram (ESD) 3.2.Constructs F-tests using expected mean squares for random and mixed effects models 3.3.Constructs appropriate simultaneous confidence intervals for contrasts 3.4.Computes sample sizes for a given design to achieve desired power. Assessment Method Homework Exams Projects 3

4 3.5.Constructs contrasts using orthogonal polynomials or other methods Level 4: Analysis: 4.1.Distinguishes between a full mathematical model and a software model. 4.2.Distinguishes among retrospective, prospective observational studies; designed studies; designed experiments Distinguishes among treatment vs classification, crossed vs nested, fixed vs random vs analytic factors; breaks down error-control into randomization, replication, and blocking; distinguishes between experimental and observational units, and sizes of units (main-plot, split-plot, ) 4.4.Distinguishes between crossing and nesting 4.5.Distinguishes between a covariate and a block factor 4.6.Separates an experimental design into treatment, error-control, and sampling structures. 4.7.Distinguishes between restricted and unrestricted forms of the model 4.8.Distinguishes, based on expected mean squares, cases for use of direct, indirect, or approximate F-tests Level 5: Synthesis: 5.1.Creates an ESD for a given (and appropriate) experimental-design scenario. 5.2.Compares randomized complete-block designs to factorial and split-plot designs 5.3.Creates appropriate summaries (tabular or graphical) based on analysis of a designed experiment Level 6: Evaluation: 6.1.Compare and contrasts different designs, decides which one to select for a given problem 6.2.Draws conclusions and makes recommendations from an analysis of an experiment. 6.3.Defends selection of experimental design. 4

5 8.0 Program outcomes and/or goals supported by this course Relationship to Program Outcomes (1 = slightly, 2=moderately, 3=significantly) Program Outcomes and/or Goals for CQAS 8.1 Advanced Certificate in Lean Six Sigma Demonstrates an solid understanding of statistical thinking and Lean Six Sigma methodology in solving real-world problems Leads Lean Six Sigma improvement projects. Level of Support Advanced Certificate and Masters of Science in Applied Statistics Demonstrates solid understanding of statistical thinking and applied statistics methodology in solving real-world problems Designs studies that are efficient and valid Analyzes data using appropriate statistical methods Communicates the results of statistical analysis with effective reports and presentations. Note: Students obtaining the Advanced Certificate in Applied Statistics will not be expected to perform at the same level as students obtaining a Master of Science degree. 5

6 9.0 - Not Applicable General Education Learning Outcome Supported by the Course, if appropriate Communication Express themselves effectively in common college-level written forms using standard American English Revise and improve written and visual content Express themselves effectively in presentations, either in spoken standard American English or sign language (American Sign Language or English-based Signing) Comprehend information accessed through reading and discussion Intellectual Inquiry Review, assess, and draw conclusions about hypotheses and theories Analyze arguments, in relation to their premises, assumptions, contexts, and conclusions Construct logical and reasonable arguments that include anticipation of counterarguments Use relevant evidence gathered through accepted scholarly methods and properly acknowledge sources of information Ethical, Social and Global Awareness Analyze similarities and differences in human experiences and consequent perspectives Examine connections among the world s populations Identify contemporary ethical questions and relevant stakeholder positions Scientific, Mathematical and Technological Literacy Explain basic principles and concepts of one of the natural sciences Apply methods of scientific inquiry and problem solving to contemporary issues Comprehend and evaluate mathematical and statistical information Perform college-level mathematical operations on quantitative data Describe the potential and the limitations of technology Use appropriate technology to achieve desired outcomes Creativity, Innovation and Artistic Literacy Demonstrate creative/innovative approaches to course-based assignments or projects Interpret and evaluate artistic expression considering the cultural context in which it was created Assessment Method 10.0 Other relevant information (such as special classroom, studio, or lab needs, special scheduling, media requirements, etc.) None 6

7 *Optional course designation; approval request date: This is the date that the college curriculum committee forwards this course to the appropriate optional course designation curriculum committee for review. The chair of the college curriculum committee is responsible to fill in this date. **Optional course designation; approval granted date: This is the date the optional course designation curriculum committee approves a course for the requested optional course designation. The chair of the appropriate optional course designation curriculum committee is responsible to fill in this date. ***Course Conversion Designations Please use the following definitions to complete table 2.a on page one. Semester Equivalent (SE) Closely corresponds to an existing quarter course (e.g., a 4 quarter credit hour (qch) course which becomes a 3 semester credit hour (sch) course.) The semester course may develop material in greater depth or length. Semester Replacement (SR) A semester course (or courses) taking the place of a previous quarter course(s) by rearranging or combining material from a previous quarter course(s) (e.g. a two semester sequence that replaces a three quarter sequence). New (N) - No corresponding quarter course(s). 7