AP CSP - UNIT 3 & 4

Unit 3:
Data Representation

By Klea h

​3.1 Binary

• ​Binary is a base-2 number system that only uses digits 1 and 0 (binary digit = bit).

• Each bit represents a dichotomous relationship: on/off, true/false, or 1/0

• Bits form the foundation of digital information. When combined (e.g., 10100110), they can represent abstractions like letters, numbers, or colors.

• dichotomous: in which something can only be one thing or another (yes or no)

• decimal system: the number system that has digits 0 - 9

3.2 Base Conversions

​ASCII: A system that uses binary codes to represent English letters and symbols. It uses 7 or 8 bits, so it can only show basic characters like A–Z, 0–9, and punctuation. ASCII represents only 128 characters.

Unicode: A newer system that uses 8, 16 or 32 bits to represent characters from many languages around the world. It represents more than 150 thousand global symbols.

• Both ASCII and Unicode show abstraction: they allow computers to work with text by mapping binary values to human-readable symbols.

Noise & Error Handling

• Noise is unwanted or corrupt data in binary communication (e.g., from poor signal).

• Computers use error detection and correction algorithms to keep data accurate.

Example

BLUE =
01000010 01001100 01010101 01000101

B --> 01000010
L --> 01001100
U --> 01010101
E --> 01000101

3.5 Digitization

Two communications schemes used to convey messages digitally:

​Fixed width encoding --> every letter is represented by a specific number of bits (Example: A = 11000, B = 10011 etc.

​Variable width encoding -->

a different number of bits represents each character (Example: A = 01, B = 1000, C = 1010, D = 100 etc.

​3.6 Analog vs. Digital Data

Analog data is continuous — it changes smoothly, like sound waves, temperature, or light.

Digital data is discrete — it breaks the continuous analog signal into small, countable chunks called quanta.

​ANALOG
DIGITAL

​

• Digitizing is the process of converting analog (real-world) data into binary so it can be processed.

  • Example: A digital thermometer reads specific values (e.g., 98.6°F), while an analog thermometer moves smoothly.

• Digitizing process is an example of abstraction:

  • It removes infinite real-world details and captures just enough to represent the information meaningfully.

• Digital data = simplified version of the real world that allows for efficient storage, processing, and sharing.

• ​list: an ordered sequence of elements. For example, [5, 6, 12, -98] 

• element: an individual value/item in a list.

• index value: the representation of the location of each item in a list.

• data structure: a particular way of organizing and storing data such as an array, table, etc. 

• data abstraction: help manage complexity in programs by giving a collection of data a name without referencing the specific details of the representation.

​LIST NAME

​1 2 3

​LISTS in AP CSP

​Lossless compression does not remove any data from the file.
Instead, it shrinks the non-essential elements that do not impact the picture’s quality.
You can restore the image to its initial state.

​Lossy compression significantly reduces file size by eliminating certain information. Elements considered less important can be removed from the image. As a result, you get a lighter file and a faster-loading website.

​What are Lossy and Lossless Image Compression?

There are two types of compression when optimizing your images: lossy and lossless. Lossy reduces file size by permanently removing some of the data, while lossless restores and rebuilds the image in its original form after decompression.