Syllabus

What is science?

Is it an esoteric practice that's out of the reach of ordinary mortals, or can anyone do it?

Does science deliver absolute certainty?
How do science and society interact?
What is "hypothesis testing"?
What is the role of statistics?

We'll discuss the scientific approach as one way of knowing the world, and we'll develop skills in observation, sampling methods and data analysis and use statistical analysis and dynamic modeling software.

Readings will include history and philosophy of science, original writings by various scientists, and current press reports of scientific studies and theories.

Credit may be awarded in the history and philosophy of science, research methods, statistics and computing, and the discipline of each student's project focus.

Readings

Understanding Scientific Reasoning by Ronald Giere
Cartoon Guide to Statistics by Larry Gonick and Woollcott Smith
Galileo's Commandment edited by Edmund Bolles
selected articles (class handouts).

Program topics

Week 1 (4 October): scientific questions; data description
Week 2 (11 October): models and theories; inference and falsification; probability
Week 3 (18 October): change over time
Week 4 (25 October): marginal science; characteristics of science; sampling
Week 5 (1 November): Darwin's science; confidence intervals
Week 6 (8 November): DNA and genome; Darwin and the Victorians, statistical hypotheses
Week 7 (15 November): ecology; comparing populations; correlation vs. causation
Week 8 (22 November): causal models; analysis of variance; evaluating scientific studies
Week 9 (6 December): decision making; correlation and regression
Week 10(13 December): group project presentations, potluck, overview and perspectives

Program Objectives

The overall goals of this course are to investigate the process of science and to practice evaluating the information that science delivers to our society. We will consider the different types of questions science attempts to answer and the different methods that can be used to approach these questions. We will consider historical examples including the development of the theory of evolution, and we will examine the lives and livelihoods of a few scientists. We will look at some of the mathematical language that is used both to conduct science and to communicate the results of science to various audiences. Finally, we will use various tools of the trade, from our own senses and intellect to electronic sensors and computational software, to experience the process of science, conduct our own scientific investigations, and analyze reports of scientific studies.

By the end of this program, members of this learning community will be able to communicate their own understanding of

the value of science as a way of thinking,
the fundamental assumptions on which scientific thinking are based and how these assumptions make science unique,
the role of statistical analyses in scientific research and other contexts,
the operation of social processes within science,
interactions between science, society and values, and
the major concepts in the development of scientific thought on biological evolution.

They will also be able to

make basic measurements, understand uncertainty, and consider uncertainty appropriately in the analysis of results,
apply basic statistical methods to describe data,
test simple hypotheses by creating models, conducting experiments, and analyzing data, often by utilizing computer hardware and software,
evaluate claims based on statistical hypotheses,
evaluate claims of causal relationships,
make recommendations in the face of incomplete information based on analyses of risk,
and use epistemic values to judge how 'scientific' different areas of knowledge appear to be.