Be familiar with the concept of a natural number and the set ℕ of natural numbers (including zero).
ℕ = {0, 1, 2, 3, … }
3.5.1.2 Integer numbers
Content
Additional information
Be familiar with the concept of an integer and the set ℤ of integers.
ℤ = { …, -3, -2, -1, 0, 1, 2, 3, … }
3.5.1.3 Rational numbers
Content
Additional information
Be familiar with the concept of a rational number and the set ℚ of rational numbers, and that this set includes the integers.
ℚ is the set of numbers that can be written as fractions (ratios of integers). Since a number such as 7 can be written as 7/1, all integers are rational numbers.
3.5.1.4 Irrational numbers
Content
Additional information
Be familiar with the concept of an irrational number.
An irrational number is one that cannot be written as a fraction, for example √2.
3.5.1.5 Real numbers
Content
Additional information
Be familiar with the concept of a real number and the set ℝ of real numbers, which includes the natural numbers, the rational numbers, and the irrational numbers.
ℝ is the set of all 'possible real world quantities'.
3.5.1.6 Ordinal numbers
Content
Additional information
Be familiar with the concept of ordinal numbers and their use to describe the numerical positions of objects.
When objects are placed in order, ordinal numbers are used to tell their position. For example, if we have a well-ordered set S = {‘a’, ‘b’, ‘c’, ‘d’}, then ‘a’ is the 1st object, ‘b’ the 2nd, and so on.
3.5.1.7 Counting and measurement
Content
Additional information
Be familiar with the use of:
natural numbers for counting
real numbers for measurement.
3.5.2 Number bases
3.5.2.1 Number base
Content
Additional information
Be familiar with the concept of a number base, in particular:
decimal (base 10)
binary (base 2)
hexadecimal (base 16).
Students should be familiar with expressing a number’s base using a subscript as follows:
Base 10: Number10 , eg 6710
Base 2: Number2 , eg 100110112
Base 16: Number16 , eg AE16
Convert between decimal, binary and hexadecimal number bases.
Be familiar with, and able to use, hexadecimal as a shorthand for binary and to understand why it is used in this way.
3.5.3 Units of information
3.5.3.1 Bits and bytes
Content
Additional information
Know that:
the bit is the fundamental unit of information
a byte is a group of 8 bits.
A bit is either 0 or 1.
Know that the 2n different values can be represented with n bits.
For example, 3 bits can be configured in 23 = 8 different ways.
000, 001, 010, 011, 100, 101, 110, 111
3.5.3.2 Units
Content
Additional information
Know that quantities of bytes can be described using binary prefixes representing powers of 2 or using decimal prefixes representing powers of 10, eg one kibibyte is written as 1KiB = 210 B and one kilobyte is written as 1 kB = 103 B.
Know the names, symbols and corresponding powers of 2 for the binary prefixes:
kibi, Ki - 210
mebi, Mi - 220
gibi, Gi - 230
tebi, Ti - 240
Know the names, symbols and corresponding powers of 10 for the decimal prefixes:
kilo, k - 103
mega, M - 106
giga, G - 109
tera, T - 1012
Historically the terms kilobyte, megabyte, etc have often been used when kibibyte, mebibyte, etc are meant.
3.5.4 Binary number system
3.5.4.1 Unsigned binary
Content
Additional information
Know the difference between unsigned binary and signed binary.
Students are expected to be able to convert between unsigned binary and decimal and vice versa.
Know that in unsigned binary the minimum and maximum values for a given number of bits, n , are 0 and 2n -1 respectively.
3.5.4.2 Unsigned binary arithmetic
Content
Additional information
Be able to:
add two unsigned binary integers
multiply two unsigned binary integers.
3.5.4.3 Signed binary using two’s complement
Content
Additional information
Know that signed binary can be used to represent negative integers and that one possible coding scheme is two’s complement.
This is the only representation of negative integers that will be examined. Students are expected to be able to convert between signed binary and decimal and vice versa.
Know how to:
represent negative and positive integers in two’s complement
perform subtraction using two’s complement
calculate the range of a given number of bits, n .
3.5.4.4 Numbers with a fractional part
Content
Additional information
Know how numbers with a fractional part can be represented in:
fixed point form in binary in a given number of bits.
Be able to convert for each representation form:
decimal to binary of a given number of bits
binary to decimal of a given number of bits.
3.5.5 Information coding systems
3.5.5.1 Character form of a decimal digit
Content
Additional information
Differentiate between the character code representation of a decimal digit and its pure binary representation.
3.5.5.2 ASCII and Unicode
Content
Additional information
Describe ASCII and Unicode coding systems for coding character data and explain why Unicode was introduced.
3.5.5.3 Error checking and correction
Content
Additional information
Describe and explain the use of:
parity bits
majority voting
check digits.
3.5.6 Representing images, sound and other data
3.5.6.1 Bit patterns, images, sound and other data
Content
Additional information
Describe how bit patterns may represent other forms of data, including graphics and sound.
3.5.6.2 Analogue and digital
Content
Additional information
Understand the difference between analogue and digital:
data
signals.
3.5.6.3 Analogue/digital conversion
Content
Additional information
Describe the principles of operation of:
an analogue to digital converter (ADC)
a digital to analogue converter (DAC).
3.5.6.4 Bitmapped graphics
Content
Additional information
Explain how bitmaps are represented.
Explain the following for bitmaps:
resolution
colour depth
size in pixels.
The size of an image is also alternatively sometimes described as the resolution of an image.
Size of an image in pixels is width of image in pixels x height of image in pixels.
Resolution is expressed as number of dots per inch where a dot is a pixel.
Colour depth = number of bits stored for each pixel.
Calculate storage requirements for bitmapped images and be aware that bitmap image files may also contain metadata.
Ignoring metadata,
storage requirements =size in pixelsx colour depth
where size in pixels is width in pixels x height in pixels .
Be familiar with typical metadata.
eg width, height, colour depth.
3.5.6.5 Digital representation of sound
Content
Additional information
Describe the digital representation of sound in terms of:
sample resolution
sampling rate and the Nyquist theorem.
Calculate sound sample sizes in bytes.
3.5.6.6 Musical Instrument Digital Interface (MIDI)
Content
Additional information
Describe the purpose of MIDI and the use of event messages in MIDI.
Describe the advantages of using MIDI files for representing music.
3.5.6.7 Data compression
Content
Additional information
Know why images and sound files are often compressed and that other files, such as text files, can also be compressed.
Understand the difference between lossless and lossy compression and explain the advantages and disadvantages of each.
Explain the principles behind the following techniques for lossless compression:
run length encoding (RLE)
dictionary-based methods.
3.5.6.8 Encryption
Content
Additional information
Understand what is meant by encryption and be able to define it.
Students should be familiar with the terms cipher, plaintext and ciphertext.
Caesar and Vernam ciphers are at opposite extremes. One offers perfect security, the other doesn’t. Between these two types are ciphers that are computationally secure – see below. Students will be assessed on the two types. Ciphers other than Caesar may be used to assess students' understanding of the principles involved. These will be explained and be similar in terms of computational complexity.
Be familiar with Caesar cipher and be able to apply it to encrypt a plaintext message and decrypt a ciphertext.
Be able to explain why it is easily cracked.
Be familiar with Vernam cipher or one-time pad and be able to apply it to encrypt a plaintext message and decrypt a ciphertext.
Explain why Vernam cipher is considered as a cypher with perfect security.
Since the key k is chosen uniformly at random, the ciphertext c is also distributed uniformly. The key k must be used once only. The key k is known as a one-time pad.
Compare Vernam cipher with ciphers that depend on computational security.
Vernam cipher is the only one to have been mathematically proved to be completely secure. The worth of all other ciphers ever devised is based on computational security. In theory, every cryptographic algorithm except for Vernam cipher can be broken, given enough ciphertext and time.