AP Computer Science Principles - Big Idea 2: Data

Flashcards covering key vocabulary and concepts from the AP Computer Science Principles curriculum, focusing on data representation, compression, and extraction.

Data Representation

The way a computer represents data internally is different from the way the data are interpreted and displayed for the user. Programs are used to translate data into a representation more easily understood by people.

Data Storage

Values can be stored in variables, lists of items, or standalone constants and can be passed as input to (or output from) procedures.

Bit

Shorthand for binary digit; either 0 or 1.

Byte

8 bits

Abstraction

The process of reducing complexity by focusing on the main idea, hiding irrelevant details, and bringing together related details.

Bit Abstractions

Numbers, characters, and color.

Analog Data

Data have values that change smoothly, rather than in discrete intervals, over time.

Sampling

Measuring values of the analog signal at regular intervals.

Fixed Number of Bits

Can result in overflow or other errors due to the limited range of integer values and mathematical operations.

Binary (base 2)

Uses only combinations of the digits zero and one.

Decimal (base 10)

Uses only combinations of the digits 0-9.

Data Compression

Can reduce the size (number of bits) of transmitted or stored data.

Lossless Data Compression

Can usually reduce the number of bits stored or transmitted while guaranteeing complete reconstruction of the original data.

Lossy Data Compression

Can significantly reduce the number of bits stored or transmitted but only allow reconstruction of an approximation of the original data.

Information

The collection of facts and patterns extracted from data.

Metadata

Data about data.

Cleaning Data

A process that makes the data uniform without changing their meaning.

Data Processing

Programs can be used to process data to acquire information.

Data Combination

Combining data sources, clustering data, and classifying data are parts of the process of using programs to gain insight and knowledge from data.