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Pearson Edexcel GCSE (1CP2) SLR 03 Topic 2 – Data representation

This download provides you with a zip file which contains all the resources you will need to deliver this topic.

It includes:

  • Student Learning Record Workbook (for use by students)
  • Student Learning Record Answers (for use by teachers)
  • End of Topic test and answers
  • Lesson PowerPoint’s for every lesson
  • Any associated answers or references sheets for class activities

This topic covers:

2.1 Binary

  • 2.1.1 understand that computers use binary to represent data (numbers, text, sound, graphics) and program instructions and be able to determine the maximum number of states that can be represented by a binary pattern of a given length.
  • 2.1.2 understand how computers represent and manipulate unsigned integers and two’s complement signed integers.
  • 2.1.3 be able to convert between denary and 8-bit binary numbers (0 – 255, -127 – 128).
  • 2.1.4 be able to add together two positive binary patterns and apply logical and arithmetic binary shifts.
  • 2.1.5 understand the concept of overflow in relation to the number of bits available to store a value.
  • 2.1.6 understand why hexadecimal notation is used and be able to convert between hexadecimal and binary.

2.2 Data representation

  • 2.2.1 understand how computers encode characters using 7-bit ASCII.
  • 2.2.2 understand how bitmap images are represented in binary (pixels, resolution, colour depth).
  • 2.2.3 understand how analogue sound is represented in binary (amplitude, sample rate, bit depth, sample interval).
  • 2.2.4 understand the limitations of binary representation of data when constrained by the number of available bits.

2.3 Data storage and compression

  • 2.3.1 understand that data storage is measured in binary multiples (bit, nibble, byte, kibibyte, mebibyte, gibibyte, tebibyte) and be able to construct expressions to calculate file sizes and data capacity requirements.
  • 2.3.2 understand the need for data compression and methods of compressing data (lossless, lossy).

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