Data in Science

This first lesson is partly about the question:

What is data?

and this course is mostly about the question:

How should we think about data in science?

Science

In astronomy, the typical cycle of actions in a scientific investigation is something like:

• propose
• observe sky, collect data
• "reduce" data
• explore and summarize reduced data, be surprised, discuss
• hypothesize
• test
• interpret, conclude, speculate
• report
• propose

This course concerns the parts of the investigation in bold.

Data analysis is central to the scientific process: statistical inference is the mathematical formalization of learning.

The formalism is important: that middle part of the cycle is potentially very messy.

Data

We'll come back to the question of "what is data?" at the end of session 2.

For now, note that you already have an unarticulated but likely strong sense of what data is - like many other obvious things, you know it when you see it.

One of our first tasks is to define what we mean by data mathematically - but we'll start by exploring three examples of data in astronomy.