AP Computer Science Principles Unit 2 Essentials

At the lowest level, computers store everything — numbers, text, images, sound — as bits (0s and 1s). Numbers are written in binary, and a crucial fact is that n bits can represent 2ⁿ different values, so each added bit doubles the possibilities (and too large a value causes overflow). Because bits are an abstraction, the same sequence can mean completely different things depending on how a program interprets it, and continuous analog signals become digital through sampling.

Data compression shrinks the number of bits needed to store or send data. Lossless compression removes redundancy so the original is fully recoverable (ZIP, PNG), while lossy compression permanently discards less-important detail for a much smaller size (JPEG, MP3). The central tradeoff: lossless preserves everything but shrinks less; lossy shrinks more but loses quality — so you choose based on whether any loss is acceptable.

Data becomes information only when it is analyzed to reveal patterns and insight. Programs filter, sort, aggregate, and visualize data — often using metadata (data about data) — and can handle datasets far too large for a person. But conclusions require care: data should be cleaned of errors first, and correlation does not imply causation — an association is not proof that one thing causes another.