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Biology Curriculum
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Selected tags:
#data
Be familiar with the assumptions of independence, linearity and homoscedasticity
Calculate and understand correlations, linear regression, analysis of variance
Delegate appropriate tasks both in lab and field settings to complete assignments on time.
[
BIOL 3623
]
Design an experiment to study cell biology topics
[
BIOL 2020
]
Experience in using statistical computing software
[
BIOL 4062
]
Extend the concept of trade-offs to local adaptation and the evolution of specialists and generalists (and, as always, interpret evidence)
[
BIOL 3044
]
Familiarity with diagnostic bacterial identification (catalase test, differential media, antibiotic sustainability)
[
BIOL 2004
]
Familiarity with the mess that is real data
[
BIOL 4062
]
Generate a simple scientific paper based on their field work
[
BIOL 2605
]
Generate and interpret data collected from experiments in the laboratory and communicate results by a variety of written forms.
[
BIOL 2030
]
Identify patterns in graphs related to basic phytoplankton/zooplankton population growth (Lab)
[
MARI 3602
]
Know the process to bring in Garmin GPS data into ArcGIS
[
BIOL 3633
]
Learn the difference between Raster and Vector Data Models
[
BIOL 3633
]
Practice behavioural observations
[
BIOL 2003
]
Relate graphical representations of multiple stable states to empirical examples
[
BIOL 3069
]
Synthesize the information collected during production site visits (Field trips)
[
MARI 3602
]
Understand how to manipulate/add/drop attribute data in ArcGIS
[
BIOL 3633
]
Understand the basics of probability theory, formal statistical inference and hypothesis testing
[
BIOL 3633
]
Understand the concepts and principal methods of multivariate analysis
[
BIOL 4062
]
Understand the goals of data analysis
[
BIOL 4062
]
Understand the importance of Metadata and how to add it to GIS Data
[
BIOL 3633
]
Write three formal laboratory reports (Lab)
[
MARI 3602
]
Able to use statistical computing software
[
BIOL 4062
]
Analyse statistically fish growth data collected in a class run experiment (Lab)
[
MARI 3602
]
Analyze data using basic statistical techniques (mean, standard deviation, n, chi-square test).
[
multiple courses
]
Analyze pilot data to estimate sample size/replication to ensure adequate precision for sample estimates, or power for statistical tests to compare means, in sampling/experimental designs
[
BIOL 4061
]
Collect both quantitative and qualitative data through careful observations
[
multiple courses
]
Construct linear additive models and ANOVA tables for simple and complex analyses
[
BIOL 4061
]
Describe standard experimental layouts and associated analytical models
[
BIOL 4061
]
Explain expected mean squares and their use in identifying error terms in ANOVA
[
BIOL 4061
]
Explain pseudoreplication and ways of avoiding it in ecological field experiments
[
BIOL 4061
]
Explain the relationships between Type I and Type II error, variance, replication, and effect size
[
BIOL 4061
]
Familiar with the criticisms of hypothesis testing
[
BIOL 4062
]
Familiarity with information-theoretic model selection
[
BIOL 4062
]
Familiarity with statistical likelihood and its uses
[
BIOL 4062
]
Generate and interpret appropriate tables and graphs used to represent data
[
BIOL 2020
]
Identify common pitfalls in experimental design that lead to confounding effects
[
BIOL 4061
]
Identify methods of testing assumptions and transforming data to meet assumptions
[
BIOL 4061
]
Identify non-parametric analogues of parametrical models
[
BIOL 4061
]
Identify the appropriate use of t-tests for independent and non-independent data
[
BIOL 4061
]
Infer the phylogenetic history of organisms from simple data sets.
[
BIOL 2040
]
Interpret data (e.g., graphs and tables) to assess hypotheses and generate conclusions
[
multiple courses
]
Interpret phylogenetic trees
[
multiple courses
]
Report data using written descriptions, graphs, tables, and sketches
[
multiple courses
]
State assumptions of parametric statistical models and explain the consequences of violating them
[
BIOL 4061
]
Use mathematical analysis to evaluate the effects of interspecific competition and to determine population size and growth patterns.
[
BIOL 1011
]
Use raw data to produce summary statistics and plots
[
BIOL 2003
]
Write-up the analysis of real data
[
BIOL 4062
]
Account for the stochasticity of working with live organisms in interpreting experimental data (Lab).
[
BIOL 2040
]
Apply simple statistical tests to experimental data (Lab).
[
BIOL 2040
]
Argue for or against interpretations of major events in vertebrate history(dinosaur endothermy, origin of flight, relationships between fin types etc.)
[
BIOL 3326
]
Collect qualitative and quantitative data and interpret the experimental results
[
multiple courses
]
Compare different methods of analyzing single nucleotide polymorphisms, and detail how they can be used in population genetic analyses.
[
BIOL 3042
]
Conduct regression analysis and t-tests on ecological data
[
BIOL 2060
]
Demonstrate scientific quantitative skills, such as the ability to evaluate experimental design, read graphs and understand information from scientific papers
[
BIOL 4050
]
Evaluate scientific data, opinions and theories with respect to a scientific or conservation question.
[
BIOL 3090
]
Explain how genetic correlations and tradeoffs arise and interpret empirical evidence.
[
BIOL 3044
]
Generate and interpret appropriate tables and graphs to represent ecological data
[
BIOL 2060
]
Generate appropriate tables and graphs to represent data (Lab)
[
MARI 3602
]
Generate appropriate tables and graphs to represent data (Lab).
[
BIOL 2040
]
Perform a one-way ANOVA
[
BIOL 3044
]
Present (orally) a concise representation of a data set from an original research article
[
BIOL 4020
]
Utilize PRIMER-E statistical software to analyze patterns of species abundance from a rocky shore
[
BIOL 3664
]
Write formal laboratory reports
[
BIOL 3050
]
Analyze and display a variety of ecological biologging data using multiple statistical techniques and data processing tools.
[
BIOL 4323
]
Analyze field data and evaluate the efficacy of scuba-based procedures.
[
BIOL 3680
]
Compile a data report to document a field study.
[
BIOL 3622
]
Compile, use and manipulate class data from field trip sampling and laboratory analyses to answer assignment questions
[
BIOL 3623
]
Complete a plant ecology study: develop objectives, plan the sampling design, collect data, communicate the results and write a report.
[
BIOL 3066
]
Comprehend the complexity of homology relationships under a variety of different molecular evolutionary processes.
[
BIOL 3046
]
Conduct a manipulative field experiment and analyze and interpret the results in the form of a scientific paper
[
BIOL 3761
]
Conduct correlation analysis, t-tests and regression on ecological data
[
BIOL 3069
]
Demonstrate the relationship between critical thinking and good scholarship within a course project.
[
BIOL 3046
]
Describe methods of estimating population abundance, as well as the underlying data needed. Estimate population abundance using a simple formula.
[
BIOL 3080
]
Design and conduct a field study of birds, analyze data, and interpret results.
[
BIOL 3622
]
Develop and use different methods and analyses for sampling plant communities.
[
BIOL 3066
]
Discover the positive and negative tree-crops-soil interactions (for light, water, and nutrients).
[
BIOL 3634
]
Generate a formal population or stock assessment using different population growth models and assessment methods
[
BIOL 3063
]
Interpret F-statistics on population structure and explain how deviations from the Island Model assumptions affect interpretations
[
BIOL 3042
]
Know mechanisms for functional divergence at the molecular level that span a wide range of biological complexity. Understand how specific models of adaptive evolution explain real examples of functional divergence.
[
BIOL 3046
]
Read and interpret scientific papers presenting studies or theory in plant ecology.
[
BIOL 3066
]
Summarize key features of model-based clustering approaches to estimating population structure and gene flow
[
BIOL 3042
]
Understand how explicit models of population genetic processes serve as the theoretical foundation for microevolution. Apply these models to understand different mechanisms of evolution acting on real biological data.
[
BIOL 3046
]
Understand how molecular evolutionary processes give rise to patterns of genetic diversity that we observe in the natural world, and how to use those patterns to make inferences about different processes.
[
BIOL 3046
]
Understand the importance of molecular evolution in the post-genomic era, and be able to explain this to non-specialists.
[
BIOL 3046
]
Use ecological theory to interpret empirical case studies of population dynamics
[
BIOL 3069
]
Use knowledge of molecular evolution for clear and explicit communication and exchange of ideas about the topic within a course project.
[
BIOL 3046
]
Write a formal essay synthesizing the results of scientific studies
[
BIOL 3069
]
Write research reports based on data analysis and interpretation.
[
BIOL 3060
]
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