Contact

Phone: 470-578-6546

Email: ngreen62@kennesaw.edu

Office Location: SC 331

Office Hours:
M 10:00 AM - 12:00 PM; T 9:00 AM - 11:00 AM; Other times by appointment.

Courses

For up to date course information, please see the KSU Dynamic Schedule.

Current students: please refer to D2L for current course content.

BIOL 3310: Invertebrate Zoology

Fall 2020 syllabus

Catalog description: This course is a survey of invertebrate animals. Students will explore the varied range of anatomical, physiological, and ecological relationships among these organisms in order to develop an understanding of evolutionary processes that brought about present day patterns in the biodiversity of animal phyla. In lab, students will collect, observe and identify common invertebrate taxa, and relate observed adaptations of form and function to habitat.

BIOL 4350: Comparative Vertebrate Anatomy

Fall 2023 syllabus

Catalog description: Students will explore a survey of representative vertebrates and related chordates emphasizing phylogeny and anatomical adaptations. Students will investigate evolutionary trends in the context of large-scale environmental changes that have occurred over geologic time. Using a comparative, systems-based approach, students will explore the relationships between structure and function. In the lab, students will learn to dissect selected vertebrate organisms and study anatomical adaptations among these representative models to recognize the relationships between form and function.

BIOL 6490: Special Topics - Applied Biological Data Analysis

Fall 2023 syllabus

Click here for the course website with code and data examples (external).

Catalog description: This course is a survey of data analysis skills and statistical methods that are essential for modern biology. The course takes a holistic approach to the data analysis workflow in biology using the open source environment R, including data management, exploratory data analysis, data modeling, and reproducible science practices. Statistical topics covered include generalized linear models, mixed effects models, non-linear models, and ordination. Students are required to apply techniques learned in class to real or simulated biological datasets as a course project.

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