Data
Data are the observations and measurements collected during an investigation, recorded so they can be organized, analyzed, and shared.
Definition
Data are the facts you collect during an experiment: the numbers you measure and the things you notice, written down as you go. They include quantitative measurements (numbers with units) and qualitative descriptions, and raw data are organized into tables and then analyzed with averages and graphs to find patterns that support or challenge the hypothesis. Every measurement carries an implicit uncertainty set by the instrument and method, so sound practice records raw values with units, resolution, time, and conditions before any processing, allowing later analysis choices to be audited and repeated. Data become evidence only when they are interpreted in relation to a specific claim.
Example
Measuring a bean plant daily yields Day 1, $2\ \text{cm}$; Day 2, $2.5\ \text{cm}$; Day 3, $3.1\ \text{cm}$; plus a note that the leaves turned dark green. A ramp investigation produces roll distances of $41$, $43$, $42\ \text{cm}$ at $10^\circ$; $78$, $80$, $79\ \text{cm}$ at $20^\circ$; and $112$, $115$, $110\ \text{cm}$ at $30^\circ$, with means of $42$, $79$, and $112\ \text{cm}$. A careful notebook entry logs raw stopwatch readings of $25.3$, $27.1$, and $26.4\ \text{s}$ at a probe-measured $30.2^\circ\text{C}$, with the processed mean of $26.3\ \text{s}$ written separately so the raw readings survive any re-analysis.
Key Insight
Data are what happened, not what you think about it, so record them right away before you start to interpret. Keep the raw measurements as well as the averages, because the mean hides the spread that tells you how much to trust it. Data are not self-explaining: the same numbers can support different conclusions depending on the analysis, which is why scientists report their methods alongside their results.