Dynamic aspects of living systems. Broad exposure to cellular metabolic pathways, intermediary metabolism and its regulation and bioenergetics.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, Summer
- Pre-Requisite(s): BL 3020
Using a problem-based learning approach, course examines the physiology of the human body. In-class case-study analyses provide in-depth learning about the cardiovascular and pulmonary systems and their relationship with other organ systems. Promotes development of problem-solving skills.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Pre-Requisite(s): BL 2020
A discussion of recent developments in physiology. Recent offerings have included respiratory physiology, renal physiology, clinical cardiology, and neurophysiology.
- Credits: variable to 10.0; Repeatable to a Max of 10
- Semesters Offered: Fall, Spring, Summer
- Restrictions: Permission of instructor required; Must be enrolled in one of the following Level(s): Graduate
Covers simple, multiple, and polynomial regression; estimation, testing, and prediction; weighted least squares, matrix approach, dummy variables, multicollinearity, model diagnostics and variable selection. A statistical computing package is an integral part of the course. Some prior experience with R is expected.
- Credits: 3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered: Fall, Summer
- Pre-Requisite(s): MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701
Covers construction and analysis of completely randomized, randomized block, incomplete block, Latin squares, factorial, fractional factorial, nested and split-plot designs. Also examines fixed, random and mixed effects models and multiple comparisons and contrasts. The R programming language is an integral part of the course.
- Credits: 3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered: Spring, Summer
- Pre-Requisite(s): MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701
Introduction to design, conduct, and analysis of statistical studies, with an introduction to statistical computing and preparation of statistical reports. Topics include design, descriptive, and graphical methods, probability models, parameter estimation and hypothesis testing.
- Credits: 3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered: Fall, Spring, Summer
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
A systematic survey of classical and contemporary research topics in human cognition, including perception, attention, mental representation and processing, memory, knowledge, visual imagery, problem solving, reasoning, and decision making. Students will read original research papers and develop a research proposal.
- Credits: 3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered: On Demand
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
An overview of data analysis methods including visualization, data programming, and univariate statistics such as t-test and ANOVA.
- Credits: 3.0
- Lec-Rec-Lab: (0-2-2)
- Semesters Offered: Fall, in even years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
Course covers multivariate statistics such as ANCOVA, Multiple Regression, factor analysis, clustering, machine learning, and mixture modeling.
- Credits: 3.0; Repeatable to a Max of 12
- Lec-Rec-Lab: (0-2-2)
- Semesters Offered: Spring, in even years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): PSY 5110