26 courses with the subject APM, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
Three hours of lecture/discussion per week. Algebraic operations on polynomials and rational functions as expressions, in equations, or inequalities. Graphing of linear and polynomial equations. An emphasis is placed on algebraic operations of expressions with rational exponents. Fall.
OR 3-4
Three hours of lecture/discussion per week. Course meets the SUNY general education requirement for mathematics. Elements of analytic geometry. Emphasis on the concepts of polynomial and rational functions, exponential and logarithmic functions, trigonometry and trigonometric functions and their application to design and life and management sciences. Fall and Spring. Prerequisite: Three years of high school mathematics.
Four hours of lecture per week. Introduction to calculus for students in the life and management sciences. Elements of analytic geometry, functions and their graphs, with an emphasis on the concepts of limits, and differentiation techniques for algebraic, exponential and logarithmic functions and their application to economics, and the life and management sciences. Some multivariable calculus including constrained optimization. Fall and Spring. Prerequisite: Precalculus or 3 1/2 years of high school mathematics. Note: Credit will not be granted for APM 105 after successful completion of MAT 284, MAT 285, or MAT 295 at SU. "
Four hours of lecture per week. A continuation of calculus for students in the life and management sciences. Elements of analytic geometry. An introduction to integration and applications of the definite integral. Differentiation and integration of trigonometric functions. Applications of first order differential equations and partial derivatives. Spring. Prerequisite: APM 105 or permission of the instructor. Note: Credit will not be granted for APM 106 after successful completion of MAT 286 or MAT 296 at SU.
A one semester course in differential and integral calculus. An emphasis on the concepts of limits, differentiation and integration techniques for algebraic, exponential, logarithmic functions, and trigonometric functions. This course is not intended for students that plan on taking additional Calculus courses. Offered in fall and spring. Credits will not be granted for APM 115 after SUNY ESF | 304 | Course Catalog
1 hour review of essential algebra skills needed for success in Precalculus. Topics include simplifying expressions, exponent rules, polynomial operations, factoring techniques, and solving linear, rational, radical, and quadratic equations. Emphasis is placed on building accuracy, reinforcing algebraic structure, and correcting common errors.
Essential Trigonometry for Calculus (1 credit) An online exploratory review of the trigonometric concepts essential for calculus, including the unit circle, identities, equations, graphs, and inverse functions. Emphasizes interactive learning and conceptual understanding.
A one credit hour core skills lab needed for success in Calculus. Topics include function fundamentals, rates of change and linear functions, quadratic and polynomial behavior, rational functions, and exponential and logarithmic models.
Four hours of lecture/discussion per week. Analytic geometry, limits, derivatives of functions and equations, optimization, rates, graphs, differentials, mean-value theorem, and applications of the derivative. Fall. Prerequisite: APM 104 or permission of instructor.
Four hours of lecture/discussion per week. This course is a one semester continuation of differential calculus. Integral calculus is used to describe growth and size. Topics include: techniques of integration and their application, convergence of sequences and series, separable and first-order differential equations, and polar coordinates. Spring. Prerequisite(s): Successful completion of a differential calculus course such as APM205 or MAT295.
Natural Sciences and Scientific Reasoning*
4 hours of lecture/discussion per week. Topics include vectors three dimensions, analytic geometry of three dimensions, parametric curves, partial derivatives, the gradient, optimization in several variables, multiple integration with change of variables across different coordinate systems, line integrals, and Green's Theorem. Fall and Spring. Prerequisites: Completion of Differential and Integral Calculus with at least a C-; APM206 / MAT296, or the equivalent Note: Credit cannot be given for both APM307 and MAT397.
Professional Experience: ECH 498 2 ECH 304 + ECH 306
This is a one semester course on Ordinary Differential Equations (ODE’s). Three contact hours per week (in person or online- sync) The course will cover numerical, geometric, and explore algebraic solutions to mainly first and second order ODE’s, and higher order ODE’s. We will study techniques of Laplace Transformations, System of ODE’s, series solutions, and selected topics of Linear Algebra as needed to solve systems of ODE’s. Prerequisite include APM 307. Credits will not be given for both APM485 and MAT412 or MAT485.
Three hours of lecture per week. Applications of descriptive and inferential statistics to natural resource problems. Basic concepts and techniques of estimation, confidence intervals, and hypothesis testing applied to one- and two-sample settings, paired designs, simple linear regression and correlation, contingency tables, and goodness of fit tests. Statistical software used to enhance data analysis skills. Fall. Prerequisite(s): Graduate standing.
Three hours of lecture per week. Analytical solutions of parabolic, hyperbolic and elliptic partial differential equations which appear in science and engineering. Numerical and approximate methods of solution. Spring.
Three hours of lecture per week. This course provides a rigorous introduction to calculus-based probability and statistical theory, with applications primarily drawn from engineering and the environmental sciences. Topics include: descriptive statistics and data presentation, probability, the theory and use of discrete and continuous probability distributions, confidence intervals, classical and distributional hypothesis testing, and regression analyses. Spring. Prerequisite(s): One year of Calculus. Note: Credit will not be granted for both APM 395 and APM 595.
Three hours of lecture per week. Designing and analyzing experiments and observational studies; completely randomized, split plot, randomized complete block, and nested experiment designs; single-factor, factorial, and repeated measures treatment designs; expected mean squares and variance components; fixed, random, and mixed effects models; multiple comparison and contrast analyses; analysis of covariance; statistical computing. Spring. Prerequisites: Graduate status and an introductory course in statistics covering material through the one-way analysis of variance.
SUNY ESF | 248 | Course Catalog
Three hours of lecture per week. Topics include review of basic statistical concepts and matrix algebra, classical simple and multiple linear regression models, indicator or dummy variables in regression, residual analysis, transformation and logistic regression, weighted least squares, influence diagnostics, multicollinearity, nonlinear regression models, linear mixed models, statistical computing using SAS and interpretation of results. Fall. Prerequisite: APM 391 or equivalent.
Three hours of lecture per week. Topics include review of basic statistical concepts and matrix algebra, multivariate normal distribution, Hotelling's T 2, multivariate analysis of variances, principal component analysis, factor analysis, discrimination and classification, cluster analysis, and canonical correlation analysis, statistical computing using SAS and interpretation of results. Spring. Prerequisites: APM 391 or equivalent.
Three hours of lecture per week. Topics include: review of basic statistics, sign and ranked sign tests, median and Wilcoxon tests, binomial tests, x 2-test and contingency tables (with correspondence analysis), goodness-of-fit, nonparametric correlation and association analysis, nonparametric and robust regression, generalized linear models (Logistic and Poisson regression), and re-sampling methods (bootstrapping and cross-validation), statistical computing using SAS and interpretation of results. Fall. Prerequisite: APM 391 or equivalent.
One hour of lecture per week.Statistical concepts and methods for quantifying the accuracy of maps. Sampling design and analysis for assessing accuracy of categorical attributes (e.g. land cover) is emphasized, with some discussion of continuous variables. Spring, even numbered years.
Experimental and developmental courses in areas of quantitative methods not covered in regularly scheduled courses. A course syllabus will be available to students and faculty advisors prior to registration. Fall or Spring.
Three hours of lecture per week. Topics include: review of basic regression modeling techniques, theory of generalized linear models and techniques (e.g. Logistic, Poisson and Beta regression), quantile regression, linear and nonlinear mixed models, variogram and kriging, spatial regression models (e.g., spatial lag and spatial error models), local spatial statistics and models (geographically weighted regression), statistical computing using SAS, and interpretation of results. Spring. Prerequisite: APM 630 or equivalent BPE - BIOPROCESS ENGINEERING
Source: SUNY College of Environmental Science and Forestry's catalog, linked per course · table learning_unit · CourseShelf publish 61
