CHEE209F2023Syllabus
.pdf
School
Queens University**We aren't endorsed by this school
Course
CHEE 209
Subject
Chemistry
Date
Dec 16, 2024
Pages
12
Uploaded by HighnessMask24314
Page 1 of 12 CHEE 209 – ANALYSIS OF PROCESS DATACourse Syllabus –Fall 2023 This is your course syllabus. Please download the file and keep it for future reference. LAND ACKNOWLEDGEMENTQueen's University is situated on traditional Anishinaabe and Haudenosaunee Territory. See: http://www.queensu.ca/encyclopedia/t/traditional-territories INCLUSIVITY STATEMENTQueen’s students, faculty, and staff come from every imaginable background –small towns and suburbs, urban high rises, Indigenous communities, and from more than 100 countries around the world. You belong here: https://www.queensu.ca/inclusive/. TEACHING TEAM COURSE INSTRUCTORLaurence Yang, PhD Department of Chemical Engineering Queen’s UniversityE-mail: laurence.yang@queensu.ca Office hours: By appointment
CHEE 209 –Analysis of Process Data Fall 2023 Page 2 of 12 TEACHING ASSISTANTIman MoshiritabriziE-mail: im52@queensu.ca Office hours: By appointment Jakob StraznickyE-mail: j.straznicky@queensu.ca Office hours: By appointment Alaa El HalabiE-mail: alaa.e@queensu.ca Office hours: By appointment Course Authors: P. James McLellan and Laurence Yang.
Page 3 of 12 CHEE 209 (W 3-0-0.5 3.5) COURSE DESCRIPTIONStatistical methods for analyzing and interpreting process data are discussed, with special emphasis on techniques for continuous improvement of process operations. Topics include: role of data in assessing process operation, identifying major problems, graphical and numerical summaries, principles of valid inference, probability distributions for discrete and continuous data, process capability, comparing process performance to target values, comparting performances of two processes, control charges and an introduction to linear regression analysis. Prerequisites: APSC171 (Calculus I), APSC172 (Calculus II), APSC174 (Introduction to Linear Algebra) (27/0/0/15/0) (Mathematics/Natural Sciences/Complementary Studies/Engineering Science/Engineering Design) PRE-REQUISITE KNOWLEDGEThis course is designed for learners with background in calculus and linear algebra. COURSE LEARNING OUTCOMES (CLO) By the end of this course, students should be able to: CLO DESCRIPTIONINDICATORCLO 1 Summarize, visualize and interpret data using quantitative and graphical methods.KB-Mathematics KB-ES-ApplMath (b) CLO 2 Apply simple discrete probability models to analyze data related to quality such as particle size, and to evaluate risk factors such as safety and environmental compliance. KB-ES-ApplMath (b) PA-Formulate CLO 3 Apply continuous probability models to assist in decision-making with applications to quality improvement, resource estimation, safety and environmental compliance.KB-Mathematics PA-Evaluate CLO 4 Formulate confidence intervals and hypothesis tests for mean and variance using standard conditions, with applications including decision-making for quality improvement.KB-Mathematics CLO 5 Develop, estimate and analyze linear regression models to describe and predict process and laboratory behaviour.KB-ES-ApplMath (b) PA-Formulate PA-Evaluate ET-Apply CLO 6 Use computer software to solve statistical problems.PA-Evaluate ET-Apply
Page 4 of 12 COURSE EVALUATION ASSESSMENT WEIGHTING Assessment Tool Due Date (before 23:59 ET) Weight Alignment with CLOs Quiz 1 (50 minutes, OnQ) Week 5 15% 1, 2, 3 Quiz 2 (50 minutes, OnQ) Week 7 15% 2, 3, 4 Quiz 3 (50 minutes, OnQ) Week 10 15% All CLOs Project (individual) Day 7 of Week 11 (before 23:59 ET) 10% All CLOs Final Exam 45% All CLOs 100% ASSESSMENT DESCRIPTIONSQuizzes There are three quizzes in this course. These quizzes are taken on the course website. Once you initiate the quiz, you have 50 minutes and one attempt to complete the quiz. These quizzes test your understanding and ability to apply key concepts, terminology, and techniques. In addition, online practice quizzes will be available to test your knowledge. These practice quizzes do not contribute to your grade. There will be an individual data analysis project in which you will analyze data, propose and estimate models as appropriate, make inferences and draw conclusions, while providing justification and critical assessment of the approaches you use. This project will require you to use the statistical software outlined for the course. Final Exam The final exam is closed book. Students must write their exam on the day and time scheduled by the University. You should not schedule vacations, travel, etc. during the exam period. The Term and Session Dates will indicate the final exam period session dates in each term. GRADINGAll assessments in this course will receive numerical percentage marks. The final grade you receive for the course will be derived by converting your numerical course average to a letter grade according to the established Grade Point Index.
Page 5 of 12 Feedback on Assessments The teaching team will provide feedback on graded activities. You can expect feedback on your assessments within seven days of the due date. Accessing Your Final Grade Your final grades will show on SOLUS. Official transcripts showing final grades will be available on the Official Grade Release Date. Please note that in official transcripts, a mark of IN (incomplete) is considered a grade, and your transcript is released with this grade. COURSE MATERIALSRecommended Textbooks •Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, Wiley, New York (2018), 7th Edition (Note: earlier editions are acceptable). (see wiley.ca for e-copies: https://www.wiley.com/en-ca/Applied+Statistics+and+Probability+for+Engineers%2C+7th+Edition-p-9781119400363#content-section)•Miller and Freund’s, Probability and Statistics for Engineers, 8th or 9th edition, Richard A. Johnson (author). Other Material All other course material is accessible via OnQ. Required Calculator A Casio 991 is required. ONLYthis type of non-programmable, non-communicating calculator will be allowed during tests and exams.Suggested Time Commitment This course represents a study period of one semester spanning 12 weeks. Learners can expect to invest on average 7-9 hours per week in this course. Learners who adhere to a pre-determined study schedule are more likely to successfully complete the course.
Page 6 of 12 WEEKLY COURSE LEARNING OUTCOMES WeekLearning OutcomesAssessment1 MODULE 1: Data, Statistical Learning, and the Need for Statistical Tools By the end of this week, learners will be able to: •Recognize different types of data, the way data are collected, and the implications for analysis and inference [CLO1] 2 MODULE 2: Graphical and Quantitative Methods for Investigating Process Data By the end of this week, learners will be able to: •Summarize, visualize and interpret data using quantitative and graphical methods [CLO1, CLO6] 3, 4 ,5 MODULE 3: Characterizing Variability –Probability, Random Variables, and Probability Distributions By the end of this week, learners will be able to: •Describe how probability is defined in terms of outcomes, sample space, events [CLO2, CLO3] •Describe and visualize event operations (mutually exclusive, independent) [CLO2, CLO3] •Describe and calculate probabilities and conditional probabilities [CLO2, CLO3] •Decide on appropriate discrete probability distributions and random variables for different applications, and their underlying assumptions (Bernoulli, Binomial, Poisson) [CLO2] •Characterize discrete probability distributions by their key parameters (Bernoulli, Binomial, Poisson) [CLO2] •Decide on appropriate continuous probability distributions and random variables for different applications and their underlying assumptions (Uniform, Exponential, Normal, Standard Normal) [CLO3] •Characterize continuous probability distributions by their key parameters (Uniform, Exponential, Normal, Standard Normal) [CLO3] •Make assessments by calculating probabilities [CLO2, CLO3, CLO6] Quiz 1 [CLO1] [CLO2] [CLO3] (Week 5)
Page 7 of 12 WeekLearning OutcomesAssessment6, 7, 8 MODULE 4: Characterizing Variability and Patterns from Data –Statistics and Inference By the end of this week, learners will be able to: •Describe and develop the sampling distribution for the Sample Average when the population variance is known [CLO4] •Describe the sampling distribution for the Sample Average when the population variance is unknown [CLO4] •Describe the sampling distribution for the Sample Variance [CLO4] •Construct confidence intervals and perform hypothesis tests for means and variances [CLO4, CLO6] •Describe Type I and Type II errors in statistical inference and the trade-offs in deciding test parameters and sample size [CLO4] Quiz 2 [CLO2] [CLO3] [CLO4] (Week 8) 9 MODULE 5: Statistical Quality Control By the end of this week, learners will be able to: •Propose and implement techniques for monitoring quality using measures of centrality of operation, and consistency [CLO4, CLO6] •Describe the trade-offs in setting up quality monitoring in terms of false alarm and failure to detect rates [CLO4] •Describe and assess process capability as it applies to process monitoring [CLO4]10, 11, 12 MODULE 6: Identifying and Estimating Systematic Relationships in Data –Linear Regression By the end of this week, learners will be able to: •Assess the existence of systematic co-dependencies and propose linear regression models [CLO5, CLO6] •Estimate parameters using least squares estimation [CLO5, CLO6] •Assess the quality of the estimated model using graphical and quantitative diagnostics [CLO5, CLO6] •Make inferences on model parameters and iterate model estimation to obtain adequate, parsimonious models [CLO5, CLO6] •Use appropriate probability distributions (Normal, Student’s t, Chi-squared, F) in support of inferences on model parameters [CLO5]Quiz 3 [All CLOs] (Week 10) Project [All CLOs] (Week 11)
Page 8 of 12 COURSE COMMUNICATION QUESTIONS ABOUT COURSE MATERIALQuestions or comments regarding the course material that can be of benefit to other students should be posted in the Q&A forum on the class website. The instructor, TAs, and students are encouraged to answer these questions directly in the discussion forum for the benefit of everyone in the course. COURSE ANNOUNCEMENTSThe instructor will routinely post course news in the Announcements section on the main course homepage on OnQ. Please sign up to be automatically notified by email when the instructor posts new information in the Announcements section. Instructions on how to modify your notifications are found in the Begin Heresection of the onQ course site. OFFICE HOURSIn addition to interaction in the Q&A discussion forums, you will have the opportunity to interact with either a TA or the instructor through office hours. CONFIDENTIAL MATTERSIf you have a confidential matter you would like to discuss with your instructor, their contact details are on the first page of this document. Expect email replies within 48 hours. ABSENCES (ACADEMIC CONSIDERATIONS)AND MISSED ASSIGNMENTSFor information on academic considerations due to extenuating circumstances, please review the information on the FEAS website. Note that unacceptable reasons include extra-curricular activities, travel plans, generally behind on schoolwork, etc. Do not schedule travel during midterms and final exams, as travel is not an acceptable reason for granting academic considerations. LATE POLICY In the event of extenuating circumstances, you must follow the policies for requesting an academic consideration (as described above). In the absence of an approved consideration request, the normal late penalty will apply as described in the assignment or any course/departmental policies. STANDARD QUEEN’S AND FEAS POLICIES NETIQUETTEIn this course, you may be expected to communicate with your peers and the teaching team through electronic communication. You are expected to use the utmost respect in your dealings with your colleagues or when participating in activities, discussions, and online communication. Following is a list of netiquette guidelines. Please read them carefully and use them to guide your online communication in this course and beyond.
Page 9 of 12 1.Make a personal commitment to learn about, understand, and support your peers. 2.Assume the best of others and expect the best of them. 3.Acknowledge the impact of oppression on the lives of other people and make sure your writing is respectful and inclusive. 4.Recognize and value the experiences, abilities, and knowledge each person brings. 5.Pay close attention to what your peers write before you respond. Think through and re-read your writings before you post or send them to others. 6.It’s alright to disagree with ideas, but do not make personal attacks.7.Be open to be challenged or confronted on your ideas and challenge others with the intent of facilitating growth. Do not demean or embarrass others. 8.Encourage others to develop and share their ideas. STUDENT CODE OF CONDUCTQueen's University values maintaining an environment free of, and will not tolerate, harassment, discrimination, and reprisal. The Student Code of Conduct applies to all students at Queen’s. It outlines the activities and behaviours that could be considered Non-Academic Misconduct (NAM). The Code also describes the NAM process and the sanctions that could be imposed on a student found responsible for a violation. All students should be familiar with the Student code of conduct and related policies on sexual violence prevention and response and harassment and discrimination prevention and response. https://www.queensu.ca/nonacademicmisconduct/policies COPYRIGHTCourse materials created by the course instructor, including all slides, presentations, synchronous and asynchronous course recordings, handouts, tests, exams, and other similar course materials, are the intellectual property of the instructor. It is a departure from academic integrity to distribute, publicly post, sell or otherwise disseminate an instructor’s course materials or to provide an instructor’s course materials to anyone else for distribution, posting, sale or other means of dissemination, without the instructor’s express consent. A student who engages in such conduct may be subject to penalty for a departure from academic integrity and may also face adverse legal consequences for infringement of intellectual property rights and, with respect to recordings, potentially privacy violations of other students. ACADEMIC INTEGRITYAs an engineering student, you have made a decision to join us in the profession of engineering, a long-respected profession with high standards of behaviour. As future engineers, we expect you to behave with integrity at all times. Please note that Engineers have a duty to: •Act at all times with devotion to the high ideals of personal honour and professional integrity.•Give proper credit for engineering workThe standard of behaviour expected of professional engineers is explained in the Professional Engineers Ontario Code of Ethics. Information on policies concerning academic integrity is available in the Queen’s
Page 10 of 12 University Code of Conduct, in the Senate Academic Integrity Policy Statement, on the Faculty of Engineering and Applied Science website, and from your instructor. Departures from academic integrity include plagiarism, use of unauthorized materials or services, facilitation, forgery, falsification, unauthorized use of intellectual property, and collaboration, and are antithetical to the development of an academic community at Queen’s. Given the seriousness of these matters, actions which contravene the regulation on academic integrity carry sanctions that can range from a warning or the loss of grades on an assignment to the failure of a course to a requirement to withdraw from the University. In the case of online or remotely proctored exams, impersonating another student, copying from another student, making information available to another student about the exam questions or possible answers, posting materials to online services, communicating with another person during an exam or about an exam during the exam window, or accessing unauthorized materials, including internet sources and using unauthorized materials, including smart devices, are actions in contravention of academic integrity. GENERATIVE ARTIFICIAL INTELLIGENCE (AI)TOOLS,LIKE CHATGPTStudents must submit their own work and cite the work that is not theirs. Generative AI writing tools such as ChatGPT are welcome in this class, provided that you cite the material that they generate. Any other use constitutes a Departure from Academic Integrity. INVALID EXAMSAn exam may be declared invalid in case of an interruption in an in-person examination; if the instructions in a remote or online exam were not followed; if the student uploads wrong materials; or if a situation arises where the integrity of the exam cannot be verified. If an exam is declared invalid, the student may be granted a re-write. ACADEMIC AND STUDENT SUPPORT Queen’s has a robust set of supports available to you including the Library, Student Academic Success Services (Learning Strategies and Writing Centre), and Career Services. Learners are encouraged to visit the Faculty of Engineering and Applied Science Current Students web portal for information about various other policies such as academic advisors, registration, student exchanges, awards and scholarships, etc. Students are also encouraged to review the information that is available in the EngQ Hub, posted in onQ. ABSENCES (ACADEMIC CONSIDERATIONS)AND ACADEMIC ACCOMMODATIONSFor academic accommodations and considerations please review the information on the FEAS website. ACCOMMODATIONS FOR DISABILITIESQueen's University is committed to working with students with disabilities to remove barriers to their academic goals. Queen's Student Accessibility Services (QSAS), students with disabilities, instructors, and faculty staff work together to provide and implement academic accommodations designed to allow
Page 11 of 12 students with disabilities equitable access to all course material (including in-class as well as exams). If you are a student currently experiencing barriers to your academics due to disability related reasons, and you would like to understand whether academic accommodations could support the removal of those barriers, please visit the QSAS website (https://www.queensu.ca/studentwellness/accessibility-services) to learn more about academic accommodations. To start the registration process with QSAS, click the Access Ventusbutton found on the Ventus student portal: https://www.queensu.ca/studentwellness/accessibility-services/ventus Ventus is an online portal that connects students, instructors, Queen's Student Accessibility Services, the Exam’sOffice, and other support services in the process to request, assess, and implement academic accommodations. To learn more about Ventus, visit A Visual Guide to Ventus for Students: https://www.queensu.ca/ventus-support/students/visual-guide-ventus-students For questions or assistancewith requesting Academic Consideration or Accommodation, contact the FEAS Program Advisor (Accommodations and Considerations) at engineering.aac@queensu.ca Every effort has been made to provide course materials that are accessible. For further information on accessibility compliance of the educational technologies used in this course, please consult the links below. EDUCATIONAL TECHNOLOGYACCESSIBILITY COMPLIANCE INFORMATIONonQ (Brightspace Learning Management System by D2L) https://www.d2l.com/accessibility/standards/ MS-Teams https://support.microsoft.com/en-us/office/accessibility-support-for-microsoft-teams-d12ee53f-d15f-445e-be8d-f0ba2c5ee68f Zoom https://zoom.us/accessibility If you find any element of this course difficult to access, please discuss with your instructor how you can obtain an accommodation. RELIGIOUS OBSERVANCEStudents in need of accommodation for religious observance are asked to speak to their professor within a week of receiving their syllabus. Note also that alternative assignments are considered a "reasonable accommodation" under the Ontario Human Rights Code. Students with questions about their rights and responsibilities regarding religious accommodation should contact the Chaplain Chaplain@queensu.ca.
Page 12 of 12 OTHER HUMAN-RIGHTS BASED ACCESSIBILITY NEEDSStudents who have accessibility needs based on human-rights covered grounds, should inform their instructors within a week of receiving their syllabus. Student can also contact the contact the FEAS Program Advisor (Accommodations and Considerations) at engineering.aac@queensu.ca for guidance. TECHNICAL SUPPORTSome basic comfort level with basic hardware and software skills are required for this course. If you require technical assistance, please contact Technical Support. SUPPORTIVE PERSONAL COUNSELLINGIf at any time you find yourself feeling overwhelmed, anxious, sad, lonely, or distressed, consider confidential personal counselling and wellness services offered by the Faculty of Engineering and Applied Science and the Queen’s student wellness services.