Data Representation Flashcards
Define the term ‘Number base’.
Number Base - the number of unique digits available in a numbering system.
Describe ‘decimal number base’.
Base 10: with 10 unique digits
0,1,2,3,4,5,6,7,8,9
Describe ‘Binary number base’.
Base 2: with 2 unique digits
0,1
Describe ‘Hexadecimal number base’.
Base 16: with 16 unique digits
0,1,2,3,4,5,6,7,8,9,A,B,C,D,E,F
Explain the purpose of using Hexadecimal.
Hexadecimal is used as shorthand, since it is easier to write and less prone to being misread (one hexadecimal digit is 4 binary digits)
How are whole numbers represented in binary?
/128/64/32/16/8/4/2/1/
/ 1 / 0 / 0 / 1 /1/1/0/0/ = 128+16+8+4 =156
How is hexadecimal used to represent whole numbers?
/128/64/32/16/8/4/2/1/
/ 1 / 0 / 0 / 1 /1/1/0/0/ 156 in binary
/8/4/2/1/ /8/4/2/1/
/1/0/0/1 /1/1/0/0/ is 9C in Hexadecimal
Define the term ‘bit’.
Bit - a single binary digit
Define the term ‘byte’.
Byte - A sequence of 8 bits
Define the term ‘kilobyte’, ‘megabyte’, ‘gigabyte’, ‘terabyte’
Kilobyte - approximately 1,000 bytes
Megabyte (MB)- approximately 1,000,000 bytes
Gigabyte (GB) - approximately 1,000,000,000 bytes
Terabyte - approximately 1,000,000,000,000 bytes
What are rules of binary addition?
1 + 0 = 1
1 + 1 = 10
1+ 1+ 1 = 11
What is overflow error?
When a system of program tries to store more data than it can handle in a fixed-size location, and crucial data is lost.
What are the ways you can apply ‘binary shift’?
Shift left 1 place = x2
Shift left 2 places = x4
Shift left 3 places = x8
Shift right 1 place = /2
Shift right 2 places = /4
Shift right 3 places = /8
Define the term ‘character set’.
Character set - a list of all characters recognised by a computer system. Each character has a corresponding code. e.g. ASCII or Unicode
Describe the ‘ASCII’ Character set.
ASCII uses 7 bits, and 128 different characters can be represented
Describe the ‘Unicode’ Character set.
Unicode uses 16 bits, and 2^16 different characters can be represented
Define the term ‘pixel’.
Pixel - (picture element) is the smallest possible unit within an image or on screen.
Define and Describe how ‘size’ and ‘colour depth’ affects ‘image file size’.
Size in pixels: Number of pixels in height and width for an image
Colour depth: Measure of how many colours are available
increasing the size and colour depth; increases image file size
How can you calculate bitmap image file size?
Bitmap image file size = Width x Height x Colour depth
Bitmap image file size (in bytes) = (Width x Height x Colour depth) / 8
How do you convert monochrome image into Binary Data?
1000100 - black white white etc.. look at document picture.
Explain what is meant by the term ‘analogue’.
Analogue signals are continuously variable, and need to be converted into digital in order to be stored and processed.
Describe sound sampling.
Sound sampling is the process of taking regular samples of the sound’s amplitude.
Describe sampling rate.
Sampling rate is a measure of how often a sample is taken (in Hz, 1 Hz is 1 sample per second)
Describe sample resolution.
Sample resolution is how many bits are required to store each sample
How can you calculate sound file size?
Sound File size = sampling rate x sample resolution x seconds
(in bytes) = (rate x resolution x seconds) / 8
Define the term ‘data compression’, and explain the need for it.
Data compression is a technique used to reduce file size, so it takes up less storage space.
This allows for easier quicker transmission across networks.
What is Huffman encoding?
Huffman encoding is a form of compression that represents commonly used characters with small bit patterns, and rarely used characters wit larger bit patterns.
Which binary digits label the left branches and right branches in a Huffman tree?
Left branch - 0
Right Branch - 1
In a Huffman tree, does the most frequent digit go at the bottom left, or the bottom right?
Most frequent digit - bottom left
Least frequent digit - bottom right
What is Run Length Encoding?
RLE is a form of compression that is effective when dealing with repetitive data. Data is stored once along with its frequency.
Give a few instances where RLE is useful.
- image files with lots of adjacent pixels having the same colour
- sounds files with long stretches of silence
Run Length Encode RRRRUUUUGGGGTTTTTJ
4R4U4G5T1J
