Glossary

Every field has its words

These are the ones Project 1 teaches, defined the way we use them in class, each with an example from our own interview dataset.

Term	Lesson	What it means
Binary variable	1.2	A variable with exactly two possible values.
Categorical variable	1.2	A variable whose values are text.
Cell	1.1	One box in the table: where a single row meets a single column.
Column	1.1	A vertical line of cells.
Dataset	1.2	Data organized into a table so it can be analyzed.
Estimate	1.0	An educated guess about the population, made from the sample.
Level of observation	1.2	What one row in a dataset stands for.
Number of observations (n)	1.2	How many observations a dataset has, written n. Also called the sample size.
Number of variables (k)	1.2	How many variables a dataset has, written k.
Numerical variable	1.2	A variable whose values are numbers.
Observation	1.2	A complete record of the characteristics we observed about one person or thing.
Population	1.0	Everything we want to know about: the whole group our question is about.
Primary data	1.0	Data you collected yourself, so you know exactly how it was made.
Row	1.1	A horizontal line of cells.
Sample	1.0	The part of the population we actually observe.
Value	1.2	A single data point.
Variable	1.2	A characteristic or question we record for each observation.

New concepts join the list as new projects publish. If a definition here ever disagrees with a lesson, tell us. The lesson wins and we fix the glossary.