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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
Keyword
Definition
data
values which can represent numbers, text, sound or graphics
graphics
data where each value represents the colour of an individual pixel
number of bits
how many binary 0s and 1s are needed to store a value
number of states
the difference between the largest and smallest value which can be stored
program instruction
value which represents part of an algorithm which a computer can execute
sound
data where each value represents the amplitude of an audio signal at a particular moment in time
text
data where each value represents a different character
2.1.2: understand how computers represent and manipulate unsigned integers and two's complement signed integers
Keyword
Definition
least significant bit
the bit furthest to the right of a binary value
most significant bit
the bit furthest to the left of a binary value
signed integer
a whole number which can be either positive or negative
two's complement
a way of using binary to represent signed integers
unsigned integer
a whole number which is greater than or equal to 0
2.1.3: be able to convert between denary and 8-bit binary numbers (0 - 255, -127 - 128)
Keyword
Definition
binary
way of representing data used by computers (base 2)
bit
single one or zero
bit value
the amount each bit is worth when working out a binary number
byte
combination of 8 ones or zeros
denary
way of representing numbers used by most humans (base 10)
two's complement binary
way of representing positive or negative numbers where the most significant bit for an 8 bit value is worth -128
unsigned binary
way of representing numbers so that the least significant bit on the right is worth 1 then each bit doubles in value as you move to the left
2.1.4: be able to add together two positive binary patterns and apply logical and arithmetic binary shifts
Keyword
Definition
arithmetic shift left
exactly the same as a logical shift left but may result in a value flipping between positive and negative if an overflow occurs
arithmetic shift right
copying the most significant bit on to the left of a binary value and discarding the bits on the right. Divides a signed or unsigned number by 2
binary addition
adding two binary values together
carry
an extra 0 or 1 which needs to be used when the result of a binary addition is more than 1
logical shift left
adding zeros on to the right of a binary value and discarding the bits on the left. Multiples the value by 2
logical shift right
adding zeros on to the left of a binary value and discarding the bits on the right. Divides the value by 2
2.1.5: understand the concept of overflow in relation to the number of bits available to store a value
Keyword
Definition
number of bits
the number of individual 0s and 1s used to store a value
overflow
a type of runtime error which occurs when a value is too big to be stored with the number of bits available
value
a number which can represent data or an instruction
2.1.6: understand why hexadecimal notation is used and be able to convert between hexadecimal and binary
Keyword
Definition
binary
a way of representing values which uses 2 different characters (0 and 1)
byte
8 bits in binary or 2 characters in hex
denary
a way of representing values which uses 10 different characters (0-9)
hexadecimal
a way of representing values which uses 16 different characters (0-9 plus A-Z)
nibble
4 bits in binary or 1 character in hex
2.2.1: understand how computers encode characters using 7-bit ASCII
Keyword
Definition
ASCII
American Standard Code for Information Interchange
character
individual letter, symbol or digit
character set
way of encoding text by using a number to represent each character
encode
way of converting data from one form into another
2.2.2: understand how bitmap images are represented in binary (pixels, resolution, colour depth)
Keyword
Definition
bitmap image
a way of representing pictures by splitting it into a grid of pixels and storing the colour of each pixel separately
colour depth
the number of bits used to represent the colour of an individual pixel
pixel
an individual coloured dot that makes up a picture
resolution
the number of pixels per inch
2.2.3: understand how analogue sound is represented in binary (amplitude, sample rate, bit depth, sample interval)
Keyword
Definition
amplitude
indication of how loud or quiet a sound is when it is sampled. Distance up or down from the horizontal axis on a diagram showing sound.
analogue sound
a continuous audio signal
bit depth
the number of bits used to record each sample
digital sound
an audio signal that has been sampled at regular intervals
sample interval
the time between each sample (1 / sample rate)
sample rate
the number of samples recorded every second (measured in Hz)
2.2.4: understand the limitations of binary representation of data when constrained by the number of available bits
Keyword
Definition
audio quality
how accurate an audio recording sounds
available bits
the number of bits that can be used to store an individual pixel or audio sample
high frequency
sounds with a high pitch that are lost in low quality audio recordings
pixellated
how you describe the look of a bitmap image when you can see individual pixels rather than a detailed picture
quantization error
the difference between a digitally sampled audio signal and the original analogue signal
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
Keyword
Definition
bit
individual 0 or 1
byte
8 bits
gibibyte
1024 x 1024 x 1024 bytes
gigabyte
1,000,000,000 bytes
kibibyte
1024 bytes
kilobyte
1,000 bytes
mebibyte
1024 x 1024 bytes
megabyte
1,000,000 bytes
nibble
4 bits
tebibyte
1024 x 1024 x 1024 x 1024 bytes
terabyte
1,000,000,000,000 bytes
2.3.2: understand the need for data compression and methods of compressing data (lossless, lossy)
Keyword
Definition
data compression
algorithm that reduces the number of bits needed to store data
jpg
lossy compression algorithm used for images
lossless compression
compression algorithm which can be reversed without any loss of quality or data
lossy compression
compression algorithm which cannot be reversed without losing some of the original quality or data
mp3
lossy compression algorithm used for sound
run length encoding
a form of lossless compression that represents each value and the number of times it repeats in order to attempt to reduce the size of a representation of data
zip
lossless compression algorithm used for any type of data
