Adam Z. Li

Lecturer
Mathematics
EMAIL: azli@bmcc.cuny.edu
Office: N-599C
Office Hours:
Phone: +1 (212) 776-6496
Expertise
Applied mathematics, probability, business statistics, data analysis and data science
Degrees
Courses Taught
- This developmental course provides an alternative and accelerated pathway to the college-level liberal arts mathematics courses. The course will focus on applications of numerical reason to make sense of the world around us. Applications of arithmetic, proportional reasoning and algebra are emphasized. This course cannot be used as a prerequisite for MAT 056 and is not suited for Science, Technology, Engineering or Mathematics (STEM) students.
Students who passed MAT 12, MAT 14, MAT 41, MAT 51, MAT 56, MAT 160, MAT 161, MAT 56.5, MAT 150.5 cannot take MAT 161.5.
Course Syllabus - This course is the first algebra course offered at the College. It includes such topics as algebraic representation, signed numbers, operations with polynomials, factoring, the solution of linear equations, the coordinate system, the solution of simultaneous linear equations of two variables, and graphing. This course is designed to prepare students for the CUNY Freshman Skills Assessment Test required for transfer to the upper division of CUNY, as well as for more advanced math courses. If a student passes MAT 12, the student should not register for MAT 51, since MAT 12 combines MAT 8 and MAT 51.
Students who passed MAT 12, MAT 14, MAT 41, MAT 51, MAT 56, MAT 160, MAT 161, MAT 56.5, MAT 150.5 cannot take MAT 161.5.
Course Syllabus - This course is the second algebra course offered at the college. It is open to students who have completed elementary algebra or its equivalent. It includes such topics as: factoring, solutions of linear and quadratic equations, trigonometric relationships, exponents, logarithms, and the graphs of quadratic equations.
Students who passed MAT 12, MAT 14, MAT 41, MAT 51, MAT 56, MAT 160, MAT 161, MAT 56.5, MAT 150.5 cannot take MAT 161.5.
Course Syllabus - This course covers basic statistics, including: measures of central tendency, measures of dispersion, graphs, correlation, the regression line, confidence intervals, the significance of differences, and hypothesis testing, including z-tests, t-tests, and chi-square tests.
Prerequisites: MAT 12, MAT 14, MAT 41, MAT 51 or MAT 161.5
Course Syllabus - 4 CRS.6 HRS.NULL LAB HRS.MAT 150.5 (Introduction to Statistics with Algebra (same as MAT 150))
- Statistics with algebra is a statistics course (4 credits and 60 hours) with an additional 30 hours focusing on elementary algebraic concepts useful in statistics. After covering the selected algebraic concepts, the course covers the study of basic statistics. It includes measures of central tendency, measures of dispersion, graphs, probability, the binomial distribution, the normal distribution, sampling distributions, the chi-square distribution, t-tests, estimation and hypothesis testing, correlation and regression.
Students who passed MAT 12, MAT 14, MAT 41, MAT 51, MAT 56, MAT 160, MAT 161, MAT 56.5, MAT 150.5 cannot take MAT 161.5.
Please note: Tuition for this corequisite course is charged by the equated credit (hours) not per credit.
Course Syllabus - This course covers basic algebraic and trigonometric skills, algebraic equations, and functions. Topics include: mathematical induction, complex numbers, and the binomial theorem.
Prerequisite: MAT 56 or MAT 56.5
Course Syllabus - This course covers statistical concepts and techniques with applications. Topics include probability, random variables, the binomial distribution, the hyper-geometric distribution, measures of central tendency, the normal distribution, precision and confidence intervals, sample design and computer projects.
Prerequisite: MAT 206 or MAT 206.5
Course Syllabus - This is an integrated course in analytic geometry and calculus, applied to functions of a single variable. It covers a study of rectangular coordinates in the plane, equations of conic sections, functions, limits, continuity, related rates, differentiation of algebraic and transcendental functions, Rolle's Theorem, the Mean Value Theorem, maxima and minima, and integration.
Prerequisite: MAT 206 or MAT 206.5
Course Syllabus - This course applies concepts of probability and statistics to large data sets using the R programming language for computation and data visualization. Topics include exploratory data analysis (both univariate and multivariate), probability and probability distributions (both discrete and continuous), hypothesis tests and confidence intervals for µ, π, and σ, Goodness-of-fit test, ANOVA, linear and logistic regression.
Prerequisite: MAT 301
Corequisite: MAT 302
Course Syllabus
Research and Projects