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Biology Curriculum
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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
Construct linear additive models and ANOVA tables for simple and complex analyses
Describe standard experimental layouts and associated analytical models
Explain expected mean squares and their use in identifying error terms in ANOVA
Explain pseudoreplication and ways of avoiding it in ecological field experiments
Explain the relationships between Type I and Type II error, variance, replication, and effect size
Identify common pitfalls in experimental design that lead to confounding effects
Identify methods of testing assumptions and transforming data to meet assumptions
Identify non-parametric analogues of parametrical models
Identify the appropriate use of t-tests for independent and non-independent data
State assumptions of parametric statistical models and explain the consequences of violating them
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