10.1 Introduction

The video at the bottom provides an introduction to this week.

Before this video, I want to mention that statistical models and modeling will get mentioned quite frequently in this week’s text. These terms are central to statistics in general. What a model does is to provide a statistical approximation of the ‘reality’ we are interested, so that by generating ‘better’ approximations we are essentially getting closer to truly understanding the ‘reality.’13 I personally like a point made by (Burnham and Anderson 2003) that all models are essentially wrong:

Fundamental to our paradigm is that none of the models considered as the basis for data analysis are the ‘true model’ that generates the biological data we observe… A model is a simplification or approximation of reality and hence will not reflect all of reality (p. 20)

References

Burnham, Kenneth P, and David R Anderson. 2003. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer Science & Business Media.


  1. Note that the description of models introduced here may not fit the philosophical worldview you feel comfortable with or subscribe to. Refer back to Section @ref{threelevels} for an earlier discussion we had about aligning methodology and philosophical viewpoints.