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Paper 1
Data Representation
Both
Representing data efficiently saves storage and bandwidth.
Key Facts
- 1 byte = 8 bits; 1 KB = 1024 bytes.
- Higher resolution increases file size.
- Sampling theorem: sample at least twice the highest frequency.
- Hex is base 16 and uses 0-9 and A-F.
Topics Covered
Binary and Hex
What you need to know
- •Convert between binary, denary, and hexadecimal.
- •Understand binary shifts for multiplying or dividing by 2.
Exam Tips
- Write down place values before converting.
Images and Sound
What you need to know
- •Image size depends on resolution and colour depth.
- •Sound size depends on sample rate and bit depth.
Exam Tips
- Include units when calculating file size.
Compression
What you need to know
- •Lossless keeps all data; lossy removes detail.
- •Explain trade-offs between quality and size.
Exam Tips
- Use examples like PNG for lossless and JPEG for lossy.
Character Encoding
What you need to know
- •ASCII uses 7 bits; Unicode covers more characters.
- •Encoding maps characters to binary patterns.
Exam Tips
- Explain why Unicode is needed for global languages.
Key Terms
bit depth
Number of bits used per pixel or sample.
sampling rate
Number of samples per second for sound.
lossless
Compression with no data loss.
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Common Exam Questions
Calculate the file size of a 4 second sound clip sampled at 44 kHz with 16-bit depth.
4 marksmediumPaper 1
Model Answer
Size = 44,000 x 16 x 4 bits = 2,816,000 bits = 352,000 bytes (approx).
What examiners want to see
- ✓Correct formula
- ✓Units
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