COURSES
I teach three courses at Texas Tech University. Two of those are graduate courses that are geared to expand the toolbox of the quantitative ecologist: Biostats in R: BIOL 6309 (taught every fall) and Advanced Quantitative Methods: BIOL 6301 section 047.
The third course is one that I rotate with other faculty: Principles of Ecology (BIOL 3309). I teach this next in Fall 2023.
The third course is one that I rotate with other faculty: Principles of Ecology (BIOL 3309). I teach this next in Fall 2023.
Biostatistics in R - BIOL 6309
Course description
This course focuses on basic experimental designs, hypothesis testing, probability, parametric and non-parametric tests, confidence intervals, t-tests, analysis of variance (ANOVA), covariance and correlation, randomization methods, fixed-effects and mixed-effects regression models, and time-permitting, will cover basics on Akaike Information Criterion, and multivariate analyses (PCA, and time-permitting NMDS).
The format is designed to provide background knowledge and understand concepts in statistics (taught Tuesdays), as well as conducting various statistical analyses in R (Thursday). This way, students are well equipped to understand and interpret the results of statistical analyses in R. No prior knowledge of R is required for this course.
Expected learning outcomes
This course focuses on basic experimental designs, hypothesis testing, probability, parametric and non-parametric tests, confidence intervals, t-tests, analysis of variance (ANOVA), covariance and correlation, randomization methods, fixed-effects and mixed-effects regression models, and time-permitting, will cover basics on Akaike Information Criterion, and multivariate analyses (PCA, and time-permitting NMDS).
The format is designed to provide background knowledge and understand concepts in statistics (taught Tuesdays), as well as conducting various statistical analyses in R (Thursday). This way, students are well equipped to understand and interpret the results of statistical analyses in R. No prior knowledge of R is required for this course.
Expected learning outcomes
- Learn how to write basic functions that can be applied to data sets
- Learn theory and concepts of statistical analyses and interpret the results
- Create publication-quality figures in R.
Advanced Quantitative Methods using R - BIOL 6301 047
Course description
The prerequisite for this advanced course is BIOL 6309 and at least one course in R (e.g. BIOL 6325 R as a Research Tool). If you have had other statistics courses and already know how to program in R and want to enroll in this course, please email me.
This course’s objective is to familiarize the students with analyses that go beyond the traditional statistics course. Among others: these include bootstrapping approaches, likelihood methods, Bayesian analyses, and optimization procedures in non-linear models. Other quantitative methods can be incorporated, depending on the needs of the students in class - thus, a course with flexibility.
Expected learning outcomes
The prerequisite for this advanced course is BIOL 6309 and at least one course in R (e.g. BIOL 6325 R as a Research Tool). If you have had other statistics courses and already know how to program in R and want to enroll in this course, please email me.
This course’s objective is to familiarize the students with analyses that go beyond the traditional statistics course. Among others: these include bootstrapping approaches, likelihood methods, Bayesian analyses, and optimization procedures in non-linear models. Other quantitative methods can be incorporated, depending on the needs of the students in class - thus, a course with flexibility.
Expected learning outcomes
- Learn how to analyze subsets of data in large data sets
- Learn how to do ordinations on community data
- Learn how to perform multivariate analyses
- Learn how to analyze non-linear data
- Learn how to analyze data that violate the assumptions of independence
- Create professional figures for use in publications
BIOL 3309 - Principles of Ecology
Course description
Ecology is the study of relationships between organisms and the environment. In this course, we will review the principle ecological and evolutionary concepts, hypotheses, and theories behind these relationships. Ecology is a very broad field, with cross-disciplinary links within and outside of biological sciences, and data from ecological studies are often used in applied settings for conservation and environmental sciences policies. Overall, we will cover topics ranging from interactions between individual organisms to interactions shaping the entire biosphere
Expected learning outcomes
Upon completion of this course, students should be able to:
Ecology is the study of relationships between organisms and the environment. In this course, we will review the principle ecological and evolutionary concepts, hypotheses, and theories behind these relationships. Ecology is a very broad field, with cross-disciplinary links within and outside of biological sciences, and data from ecological studies are often used in applied settings for conservation and environmental sciences policies. Overall, we will cover topics ranging from interactions between individual organisms to interactions shaping the entire biosphere
Expected learning outcomes
Upon completion of this course, students should be able to:
- Identify and describe major ecological principles, and explain the concepts that define the science
- Recognize and describe patterns of environmental variation across different spatial scales and the associated implications for organisms
- Identify major patterns of life-history and trait variation among organisms and be able to distinguish patterns across communities and ecosystems, within communities, or within lineages
- Explain population growth and its limits, understand various types of species interactions, and outline different models of population growth due to interactions
- Identify spatial & temporal patterns of species diversity, and hypotheses about how these patterns are formed
- Understand and describe the impacts humans have on population, communities, and ecosystem
