Computers can only understand binary (1s and 0s). Every character you type - letters, numbers, symbols - must be converted to a binary code for the computer to store and process it.

Key Idea: Each character is assigned a unique binary number. When you press 'A' on your keyboard, the computer stores its binary code, not the letter itself.

What is a Character Set?

A character set is a collection of characters that a computer can recognise and use. It defines:

Which characters are available (letters, numbers, symbols)
The binary code assigned to each character
How many bits are used per character

The Bits vs Characters Relationship

Number of characters = 2^{number of bits}

Bits per Character	Maximum Characters	Example
7 bits	2⁷ = 128	Original ASCII
8 bits (1 byte)	2⁸ = 256	Extended ASCII
16 bits (2 bytes)	2¹⁶ = 65,536	Unicode (basic)
32 bits (4 bytes)	2³² = 4+ billion	Unicode (full)

ASCII (American Standard Code for Information Interchange)

ASCII is one of the oldest and most widely used character sets. In exams, ASCII uses 8 bits per character.

ASCII Key Facts

Uses 8 bits (1 byte) per character
Can represent 256 different characters (2⁸)
Includes: uppercase letters, lowercase letters, digits 0-9, punctuation, control characters
Only supports English and basic symbols

ASCII is Logically Ordered

Characters in ASCII follow a logical sequence:

A = 65, B = 66, C = 67, D = 68...

a = 97, b = 98, c = 99, d = 100...

0 = 48, 1 = 49, 2 = 50, 3 = 51...

Exam Tip: The code for 'B' is always one more than 'A'. If A = 65, then B = 66. You don't need to memorise codes - just understand the pattern!

Try It: ASCII Lookup

Enter a character to see its ASCII code:

Unicode

Unicode was created to solve ASCII's limitations. It can represent characters from every language in the world, plus emojis and symbols!

Feature	ASCII	Unicode
Bits per character	8 bits (1 byte)	8-32 bits (1-4 bytes)
Total characters	256	Over 140,000
Languages	English only	All world languages
Emojis	No	Yes
File size	Smaller	Larger
Compatibility	Older systems	Modern systems

Trade-off: Characters vs File Size

More bits per character = more possible characters, but larger file sizes.

A text file in Unicode can be 2-4 times larger than the same text in ASCII!

Calculating Text File Size

Formula

File size (bits) = Number of characters × Bits per character

File size (bytes) = Number of characters × Bytes per character

Example: Calculate the file size of "Hello" in ASCII

Count characters: "Hello" = 5 characters
ASCII uses 8 bits (1 byte) per character
File size = 5 × 8 = 40 bits or 5 bytes

2. Representing Images

Images as Pixels

Digital images are made up of tiny squares called pixels (picture elements). Each pixel has a specific colour, represented by a binary code.

A simple 8×8 pixel image. Zoom in on any photo to see pixels!

Key Idea: The more pixels an image has, the more detail it can show - but the larger the file size.

Resolution

Resolution is the number of pixels in an image, usually expressed as width × height.

Common Resolutions

HD: 1280 × 720 = 921,600 pixels
Full HD: 1920 × 1080 = 2,073,600 pixels (about 2 megapixels)
4K: 3840 × 2160 = 8,294,400 pixels (about 8 megapixels)

Effect of Resolution

Higher Resolution	Lower Resolution
More pixels	Fewer pixels
More detail/sharper image	Less detail/blurry when enlarged
Larger file size	Smaller file size

Colour Depth

Colour depth is the number of bits used to represent the colour of each pixel.

Colour Depth Formula

Number of colours = 2^{colour depth}

Colour Depth	Number of Colours	Use Case
1 bit	2¹ = 2	Black and white only
4 bits	2⁴ = 16	Simple graphics
8 bits	2⁸ = 256	GIF images
24 bits	2²⁴ = 16.7 million	"True colour" photos

Visual Comparison

1-bit (2 colours)

8-bit (256 colours)

24-bit (16.7M colours)

Calculating Image File Size

Image File Size Formula

File size (bits) = Width × Height × Colour depth

File size (bytes) = (Width × Height × Colour depth) ÷ 8

Example: Calculate the file size of a 1920×1080 image with 24-bit colour

Total pixels = 1920 × 1080 = 2,073,600 pixels
Bits per pixel = 24 bits
Total bits = 2,073,600 × 24 = 49,766,400 bits
Convert to bytes = 49,766,400 ÷ 8 = 6,220,800 bytes
Convert to MB = 6,220,800 ÷ 1,000,000 ≈ 6.2 MB

Metadata

Metadata is additional information stored with an image file. It's "data about data".

What Metadata Includes

Image dimensions: Width and height in pixels
Colour depth: Bits per pixel
File format: JPEG, PNG, GIF, etc.
Date created: When the image was taken/created
Camera settings: For photos - aperture, shutter speed, ISO
GPS location: Where the photo was taken

Why Metadata Matters: Metadata is needed by software to correctly display the image. Without it, the computer wouldn't know how to interpret the binary data!

3. Representing Sound

Analogue vs Digital Sound

Sound in the real world is analogue - a continuous wave that varies smoothly. Computers need digital data - discrete binary values.

Analogue sound wave with digital sample points

Sampling: To store sound digitally, we take "snapshots" (samples) of the sound wave at regular intervals and convert each measurement to binary.

Sample Rate

Sample rate is how many samples are taken per second. It's measured in Hertz (Hz).

1 Hz = 1 sample per second

1 kHz = 1,000 samples per second

Sample Rate	Samples per Second	Use Case
8,000 Hz (8 kHz)	8,000	Telephone quality
22,050 Hz	22,050	AM radio quality
44,100 Hz (44.1 kHz)	44,100	CD quality
48,000 Hz (48 kHz)	48,000	DVD/professional audio

Effect of Sample Rate

Higher Sample Rate	Lower Sample Rate
More samples per second	Fewer samples per second
More accurate representation	Less accurate (sounds "choppy")
Better quality playback	Lower quality playback
Larger file size	Smaller file size

Bit Depth

Bit depth (also called sample resolution) is the number of bits used to store each sample.

Bit Depth	Possible Values	Use Case
8 bits	2⁸ = 256 levels	Basic audio
16 bits	2¹⁶ = 65,536 levels	CD quality
24 bits	2²⁴ = 16.7 million levels	Professional studio

Effect of Bit Depth

Higher bit depth = more precise volume levels = better dynamic range = larger files

Lower bit depth = fewer volume levels = more "noise" = smaller files

Duration

Duration is simply how many seconds of audio the sound file contains.

Obvious but important: A 5-minute song will have a file size 5× larger than a 1-minute song (assuming same quality settings).

Calculating Sound File Size

Sound File Size Formula

File size (bits) = Sample rate × Bit depth × Duration (seconds)

File size (bytes) = (Sample rate × Bit depth × Duration) ÷ 8

For stereo audio, multiply by 2 (two channels)

Example: Calculate the file size of a 3-minute CD-quality audio file (mono)

Sample rate = 44,100 Hz
Bit depth = 16 bits
Duration = 3 minutes = 180 seconds
File size (bits) = 44,100 × 16 × 180 = 127,008,000 bits
File size (bytes) = 127,008,000 ÷ 8 = 15,876,000 bytes
File size (MB) = 15,876,000 ÷ 1,000,000 ≈ 15.9 MB

For stereo, this would be 31.8 MB (×2 for two channels)

Quick Reference Card

Characters

ASCII: 8 bits = 256 characters
Unicode: 8-32 bits = 140,000+ characters
File size = characters × bits per char
Characters are logically ordered (A=65, B=66...)

Images

Made of pixels (picture elements)
Resolution = width × height
Colours = 2^{colour depth}
File size = width × height × colour depth
Metadata stores dimensions, format, etc.

Sound

Analogue sound → digital samples
Sample rate in Hz (44.1kHz = CD)
Bit depth = bits per sample (16-bit = CD)
File size = rate × depth × duration
Stereo = mono × 2

The Universal Trade-Off

For ALL data types: Higher quality = Larger file size

More bits per item means more possible values/detail, but more storage needed.

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