Data Representation

Question 1

Define the term ‘Number base’.

Answer 1

Number Base - the number of unique digits available in a numbering system.

Question 2

Describe ‘decimal number base’.

Answer 2

Base 10: with 10 unique digits
0,1,2,3,4,5,6,7,8,9

Question 3

Describe ‘Binary number base’.

Answer 3

Base 2: with 2 unique digits
0,1

Question 4

Describe ‘Hexadecimal number base’.

Answer 4

Base 16: with 16 unique digits
0,1,2,3,4,5,6,7,8,9,A,B,C,D,E,F

Question 5

Explain the purpose of using Hexadecimal.

Answer 5

Hexadecimal is used as shorthand, since it is easier to write and less prone to being misread (one hexadecimal digit is 4 binary digits)

Question 6

How are whole numbers represented in binary?

Answer 6

/128/64/32/16/8/4/2/1/
/ 1 / 0 / 0 / 1 /1/1/0/0/ = 128+16+8+4 =156

Question 7

How is hexadecimal used to represent whole numbers?

Answer 7

/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

Question 8

Define the term ‘bit’.

Answer 8

Bit - a single binary digit

Question 9

Define the term ‘byte’.

Answer 9

Byte - A sequence of 8 bits

Question 10

Define the term ‘kilobyte’, ‘megabyte’, ‘gigabyte’, ‘terabyte’

Answer 10

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

Question 11

What are rules of binary addition?

Answer 11

1 + 0 = 1
1 + 1 = 10
1+ 1+ 1 = 11

Question 12

What is overflow error?

Answer 12

When a system of program tries to store more data than it can handle in a fixed-size location, and crucial data is lost.

Question 13

What are the ways you can apply ‘binary shift’?

Answer 13

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

Question 14

Define the term ‘character set’.

Answer 14

Character set - a list of all characters recognised by a computer system. Each character has a corresponding code. e.g. ASCII or Unicode

Question 15

Describe the ‘ASCII’ Character set.

Answer 15

ASCII uses 7 bits, and 128 different characters can be represented

Question 16

Describe the ‘Unicode’ Character set.

Answer 16

Unicode uses 16 bits, and 2^16 different characters can be represented

Question 17

Define the term ‘pixel’.

Answer 17

Pixel - (picture element) is the smallest possible unit within an image or on screen.

Question 18

Define and Describe how ‘size’ and ‘colour depth’ affects ‘image file size’.

Answer 18

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

Question 19

How can you calculate bitmap image file size?

Answer 19

Bitmap image file size = Width x Height x Colour depth
Bitmap image file size (in bytes) = (Width x Height x Colour depth) / 8

Question 20

How do you convert monochrome image into Binary Data?

Answer 20

1000100 - black white white etc.. look at document picture.

Question 21

Explain what is meant by the term ‘analogue’.

Answer 21

Analogue signals are continuously variable, and need to be converted into digital in order to be stored and processed.

Question 22

Describe sound sampling.

Answer 22

Sound sampling is the process of taking regular samples of the sound’s amplitude.

Question 23

Describe sampling rate.

Answer 23

Sampling rate is a measure of how often a sample is taken (in Hz, 1 Hz is 1 sample per second)

Question 24

Describe sample resolution.

Answer 24

Sample resolution is how many bits are required to store each sample

Question 25

How can you calculate sound file size?

Answer 25

Sound File size = sampling rate x sample resolution x seconds
(in bytes) = (rate x resolution x seconds) / 8

Question 26

Define the term ‘data compression’, and explain the need for it.

Answer 26

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.

Question 27

What is Huffman encoding?

Answer 27

Huffman encoding is a form of compression that represents commonly used characters with small bit patterns, and rarely used characters wit larger bit patterns.

Question 28

Which binary digits label the left branches and right branches in a Huffman tree?

Answer 28

Left branch - 0
Right Branch - 1

Question 29

In a Huffman tree, does the most frequent digit go at the bottom left, or the bottom right?

Answer 29

Most frequent digit - bottom left
Least frequent digit - bottom right

Question 30

What is Run Length Encoding?

Answer 30

RLE is a form of compression that is effective when dealing with repetitive data. Data is stored once along with its frequency.

Question 31

Give a few instances where RLE is useful.

Answer 31

• image files with lots of adjacent pixels having the same colour
• sounds files with long stretches of silence

Question 32

Run Length Encode RRRRUUUUGGGGTTTTTJ

Answer 32

4R4U4G5T1J