This course provides an overview of existing psychological and epidemiological findings on the relationship between behavior and disease. The course explores how behavior, emotion and cognition can influence disease processes and examines the impact of stress and perceived control of one’s destiny on coronary, immune and infectious diseases and symptoms. The biological processes of several relevant chronic illnesses are covered as well as related racial and social economic health disparities. Templates for understanding and treating chronic illness including social support, referral and interventions for optimal physical and mental health are discussed. The interdisciplinary theme of this course will provide an overview of extant literature on theories of health psychology within the context of critical race theory, epidemiology, research methods, philosophy of science, biological anthropology, sociology, as well as applied health/medical fields for an enriched understanding of the biopsychosocial approach to health and illness. Lectures and in-class activities as well as films, guest lecturers, and interactive computer programs make up this textbook-free course with required readings made available through CityTech’s OpenLab and Open Educational Resources (OER).
Topics include systems of equations, matrices, determinants, eigenvalues and eigenvectors, inner products, vector spaces, and subspaces.
Prereq: MAT1575 (Calculus II)
Meeting Time – Mon/Wed: 1-2:15 p.m.
Text: Linear Algebra and its Applications,4th Edition by David C. Lay. Publisher: Addison Wesley.
Instructor’s name: Urmi Ghosh-Dastidar
Office Hours: Mon: 11:50 – 12:50 p.m. Wed: 4:40 – 5:40 p.m. (Namm 726)
Office: N726 ; Ph: (718)260-5349
Office: Pearl 616 (by appointment only)
If you want to meet me other than the office hours please make an appointment.
e-mail: ughosh-dastidar@citytech.cuny.edu
Note: All exams will take place in-class unless stated otherwise. The final exam date and time is fixed. You have to make yourself available for all in-class exams and final exam
Technology prerequisites: MATLAB will be used. In addition, a graphing calculator is required: We recommend a calculator which can compute eigenvalues.
E-mail:
All student must use City Tech e-mail address while taking this course. Reading e-mail on a regular basis is necessary. I may need to contact you via e-mail if situation arises. City Tech has provided all students with a City Tech email address. Your email address is the first letter of your first name, followed by your last name, followed by @campus.citytech.cuny.edu. You can access your email by going to the following web site: http://campus.citytech.cuny.edu/. For help with accessing email, you can also send an email to helpdesk@campus.citytech.cuny.edu. In case of emergency, you can call 718-254-8565 or email: epak@citytech.cuny.edu or rhoque@citytech.cuny.edu for technical help.
Theme: Biodiversity: Eco-Math link through Linear Algebra
A Brief Introduction
Biodiversity and the Hudson River
Flowing from the Lake Tear of the Clouds, North the Hudson River journeys 315 miles and drops 4,322 feet in elevation before emptying itself into New York Harbor. The Hudson River is home to diverse populations of fish, birds, and mammals that cohabit and compete among themselves for resources. Recently the American shad, Atlantic sturgeon, river herring (blue back herring and alewife), American eel, and largemouth bass are in decline. Intense economic harvesting pressure and overexploitation cause coastal and marine species to decline. Therefore, harvesting and fishing should be managed properly and carefully to avoid decline of current population. Food web analysis provides important information regarding the nature of competition among various organisms.
Cluster analysis in graph theory is a popular method to seek partition of a given data set into several clusters so that the data points within the same cluster are more similar than those belonged in the separate clusters. In this project we will use cluster analysis using the concepts of linear algebra to study the competition among various species in a given food web, in particular, competition among various Hudson River species. Students will find a partition of the competition graphs based on the Hudson River food web such that the strength of competition (for shared preys) between two clusters (two groups of predators) is as low as possible; however, the strength of competition within the same clusters is as high as possible.
Big Idea behind this project
Study and analyze Hudson River Food Web and its competition graph to interpret the strength of species competition. Particularly we will be exploring the followings:
• Which predator species are more connected than others?
• What happens if a specific species (particularly, a prey) dies out? Particularly, how does the removal of a particular species affect its predators and also the overall competition among all predator species?
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Students Learning Outcomes
1. To solve systems of linear equations using matrices.
2. To identify and use vector properties (spaces, subspaces, bases, inner product).
3. To identify properties of matrices (inevitability, eigenvalues, eigenvectors).
4. To use computer technology to solve problems.
5. To learn how to apply core mathematical concepts (particularly eigenvalues and eigenvectors) in solving real-world problems.
7. To understand interdisciplinary approach and the significance of it in real-world applications.
General Education Learning Goals
1. To understand interdisciplinary approach and the significance of it in real-world applications.
2. To address a problem and resolve the problem with scientific methods.
An introduction to solving mathematical problems on the computer using a symbolic algebra program with applications drawn from science and engineering. Topics include roots of non-linear functions, interpolation, numerical differentiation and numerical integration.
A 3 credit but 4 hour introductory course. Topics include sample space, expectation and variance, binomial, Poisson, normal, student and chi-square distributions, confidence interval, hypothesis testing, correlation and regression. Students do 3 projects, 1 individual and 2 in groups and choose one of the group projects to present at the end of the semester. The extra classroom hour is designed to facilitate a hands-on feel to the course including a heavy use of MS Excel.
