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Biology Curriculum
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#statistics
Apply simple statistics, including chi-squared and t-tests
Calculate and understand correlations, linear regression, analysis of variance
Experience in using statistical computing software
[
BIOL 4062
]
Explain statistical deviation
[
BIOL 4062
]
Familiarity with the mess that is real data
[
BIOL 4062
]
Generate a simple scientific paper based on their field work
[
BIOL 2605
]
Understand the basics of probability theory, formal statistical inference and hypothesis testing
[
BIOL 2605
]
Understand the concepts and principal methods of multivariate analysis
[
BIOL 4062
]
Understand the goals of data analysis
[
BIOL 4062
]
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
]
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 the relationships between Type I and Type II error, variance, replication, and effect size
[
BIOL 4061
]
Familiarity with information-theoretic model selection
[
BIOL 4062
]
Familiarity with statistical likelihood and its uses
[
BIOL 4062
]
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
]
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
]
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
]
Collect qualitative and quantitative data and interpret the experimental results
[
multiple courses
]
Conduct regression analysis and t-tests on ecological data
[
BIOL 2060
]
Generate appropriate tables and graphs to represent data (Lab).
[
BIOL 2040
]
Infer (calculate) genetic variance components for continuous traits from any of the major methods used to infer them (One way ANOVA, covariance among relatives, realized heritability)
[
BIOL 3044
]
Perform a one-way ANOVA
[
BIOL 3044
]
Refine writing formal laboratory report skills, including figures, tables and statistical methods
[
multiple courses
]
Utilize PRIMER-E statistical software to analyze patterns of species abundance from a rocky shore
[
BIOL 3664
]
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
]
Communicate scientific findings and personal development orally and in writing.
[
multiple courses
]
Compile, use and manipulate class data from field trip sampling and laboratory analyses to answer assignment questions
[
BIOL 3623
]
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
]
Discover the positive and negative tree-crops-soil interactions (for light, water, and nutrients).
[
BIOL 3634
]
Formulate ecological hypotheses, design and implement simple field research methods, and analyse field data using appropriate statistical techniques.
[
BIOL 3762
]
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
]
Summarize key features of model-based clustering approaches to estimating population structure and gene flow
[
BIOL 3042
]
Write research reports based on data analysis and interpretation.
[
BIOL 3060
]
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