AP CSP Unit 1: Digital Information – Complete 2025 Study Guide

AP CSP Unit 1: Digital Information – Complete 2025 Study Guide

This is your complete guide to AP CSP Unit 1: Digital Information. This unit introduces binary, data representation, compression, encoding, and the fundamental idea that **all digital information can be reduced to 1s and 0s**.

What you will learn on this page:
  • How binary numbers work (base-2)
  • How computers represent images, text, color, and sound
  • Lossless vs. lossy compression
  • Overflow, rounding, and limitations of digital storage
  • How data is measured (bits → bytes → kilobytes → …)
  • Exam-style questions and explanations
  • Practice links + tutoring help

Binary: How Computers Store Everything

Unit 1 starts with the most fundamental concept in computer science: computers only understand 1s and 0s. These 1s and 0s are called bits (binary digits).

Binary Place Values (Base-2)

The binary system works like the decimal system, but powers of 2:

  • 20 = 1
  • 21 = 2
  • 22 = 4
  • 23 = 8
  • 24 = 16
  • … and so on.

Example:

11110₂ = 16 + 8 + 4 + 2 + 0 = 30

10101₂ = 16 + 0 + 4 + 0 + 1 = 21

00110₂ = 0 + 0 + 4 + 2 + 0 = 6

This skill appears on the AP exam, though often in conceptual form rather than direct conversion.

Representing Text: ASCII & Unicode

Text is represented using numeric codes. The AP exam focuses mostly on:

  • ASCII – 7-bit encoding (128 characters)
  • Unicode – 16-bit encoding (65,536+ characters)

ASCII is limited; Unicode allows for emoji, world languages, and special symbols.

Exam Tip: If asked which encoding represents more characters, the answer is always Unicode.

Representing Images: Pixels & Color

Images are represented as grids of pixels, each containing color information stored as numbers.

Color Models

  • RGB – Red, Green, Blue values (0–255)
  • Grayscale – single brightness value

Example:

RGB(255, 0, 0) → Red

Representing Sound: Sampling

Sound is represented using sampling — taking measurements of a sound wave at regular intervals.

Two key factors:

  • Sampling rate – how often samples are taken
  • Bit depth – precision of each sample
Higher sampling rate = better quality = larger file size.

Lossless vs. Lossy Compression

Compression reduces the size of data files. Two types:

Lossless Compression

  • No data lost
  • File can be reconstructed exactly
  • Examples: PNG, ZIP, GIF

Lossy Compression

  • Some data removed permanently
  • Smaller file sizes
  • Examples: JPG, MP3, MP4
Exam Tip: Lossy removes data humans are less likely to notice.

Data Size: Bits, Bytes, & Beyond

Data sizes increase in powers of 2:

  • 8 bits = 1 byte
  • 1,024 bytes = 1 KB
  • 1,024 KB = 1 MB
  • 1,024 MB = 1 GB
  • 1,024 GB = 1 TB

Overflow & Rounding

Digital data has limits. If a number is too big to store, you get:

  • Overflow – number exceeds storage size
  • Rounding – decimals shortened to fit storage limits

AP Exam-Style Questions

Question 1

Which of the following is true about lossy compression?

  • A. It preserves all original data
  • B. It permanently removes some data
  • C. It always produces larger files
  • D. It only works on text files
Answer: B

Question 2

How many unique values can 4 bits represent?

Answer: 2⁴ = 16

📘 Continue Studying

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