Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
5 |
2 |
8 |
15 weeks |
120 hours |
Instructor
João Luis Ferreira Batista
Objective
Present and discuss the main forms of statistical inferences and their application in forest research, given the emphasis on hypothesis testing techniques of Classical Inference and Likelihood Inference.
Content
1. Scientific Inference and Statistical Inference: Scientific knowledge; Practical knowledge; Articulation between theory and empirical; Hypotheses, Models and Data; Data: Surveys and Experiments; Strength of inference; Causes: fixed factors and random factors; Bases of Inference: Design and Model; Measurement, estimation and prediction; Interpolation and Extrapolation.
2. Fundamentals of Statistical Inference: The Concept of Stochastic Models; Discrete Families: Binomial, Poisson, Negative Binomial; Continuous Families: Exponential, Gaussian, Weibull; Properties of stochastic models; Relationship between distribution families.
3. Classic Inference: Hypothesis Test: Sample distributions: Z, t, Chi-square and F; Neyman-Pearson Paradigm; Statistical Hypotheses and Inference Errors; Fisher's Hypothesis Test; Student's Test t; Chi-Square Test; Test F and analysis of experiments;
4. Classical Inference: Regression: Simple Linear Model; Multiple Linear Model; Estimates by Minimum Squares; Inference with regression models;
5. Inference by Likelihood: Stochastic Scenario and Models; Operant model, approach model and discrepancies; Likelihood Axiom; Likelihood and Estimation Function; Hypothesis Testing by Model Comparison.
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