Unit 2: Data, Statistics, and Probability

A number can be precise and still be misleading. Before trusting a result, you need to know what was measured, who or what was sampled, and what kind of claim the evidence can support.

Source lessons

1. Defining Data
2. A Brief Introduction to Statistics and Probability

The first lesson gives you the vocabulary of data. The second gives you tools for reasoning about samples, summaries, uncertainty, and probability.

What you should be able to prove

By the end of the Unit, you should be able to:

• classify useful variables and explain what they represent;
• distinguish a population from a sample;
• choose a summary statistic for a specific purpose;
• identify a source of sampling or measurement bias; and
• separate association from a causal claim.

Evidence check

Finish with Evidence Check — Audit a Statistical Claim. You will dissect a simple claim and show exactly where its evidence is strong, weak, or incomplete.

Runtime boundary

This Unit can be completed without software. Later Units will turn the same reasoning into dataframe and visualization work once the Robotnix data workbench is available.