3.3 - data representation (5 + 8)

Question 1

define a character set

Answer 1

all the characters a computer can use with their corresponding binary code used to represent each character

Question 2

why were binary codes created?

Answer 2

typing out 1s and 0s takes too long, so binary codes were created to represent each character

(you press character and it is converted into binary)

Question 3

how many bytes is one character in ASCII?

and so how many bits?

Answer 3

1 character = 1 byte

7 bits

Question 4

how many characters are there in ASCII?

Answer 4

128

Question 5

why was Unicode created?

Answer 5

for languages that used a different alphabet set to the English language

Question 6

how many characters can be represented using 8 bits?

and what would this type of character set be called?

Answer 6

256

extended ASCII

Question 7

what number codes for A to Z in ASCII?

Answer 7

65 to 90

Question 8

what number codes from a to z in ASCII?

Answer 8

97 to 122

Question 9

convert 88 into hexadecimal

Answer 9

1) do 88/16 = 5
2) calculate the remainder = 8
3) then convert 8 to hexadecimal (which is also 8)

FINAL ANSWER - 58

Question 10

what is Unicode (in terms of storage)?

Answer 10

8 to 32 bits

Question 11

what is the equation to calculate the total number of bits stored (uncompressed)?

Answer 11

7 (ASCII bits per character) x total frequency of (all) characters

Question 12

what is the equation to calculate the total number of compressed bits - huffman’s compression?

Answer 12

• addition of total bits used = x

x times by frequency

Question 13

similarities between Unicode and ASCII?

Answer 13

they both use the same codes up to 127

Question 14

why do we compress a file?

Answer 14

• it is too big for us to store or transmit to someone else

- reduce size of file on hard drive

Question 15

what happens when you compress a file?

Answer 15

the structure of the data is manipulated + the size is smaller

Question 16

what is run length encoding?

Answer 16

form of compression effective when dealing with repeating data (data stored once with amount of time it is repeated)

ie. z8

Question 17

what is lossless compression?

and give two examples

Answer 17

reduces the size of file without permanently removing data

• ie. run length encoding
• huffman coding

Question 18

what is lossy compression?

Answer 18

reduces size of file by permanently removing data
- ie. data which is thought to be redundant

• decreases quality of image to reduce size

Question 19

state two examples of lossy compression

and if applicable, how it works

Answer 19

JPEG

MP3 - removes frequencies out of human hearing

Question 20

convert 200 to hexadecimal

Answer 20

1) 200/16 = 12 = C
2) calculate remainder = 8
3) convert remainder into hexadecimal = 8

FINAL ANSWER = C8

Question 21

how do you convert between hexadecimal and denary?

Answer 21

multiply first value by 16

then multiply second by 1

add together

Question 22

convert the following to denary:

a) 9E
b) 7F
c) F3

Answer 22

a) 9 x 16 = 144
E = 14
14 x 1 = 14
144 + 14 = 158

b) 7 x 16 = 112
F = 15, 15 x 1 = 15
112 + 15 = 127

c) 15 x 16 = 240
3 x 1 = 3
240 + 3 = 243

Question 23

how do you convert between denary and binary?

Answer 23

divide the denary number by tops on the table

Question 24

convert 111 into binary

Answer 24

128 64 32 16 8 4 2 1

0 1 1 0 1 1 1 1

Question 25

how do you convert from binary to denary?

Answer 25

add up each column with a value up

Question 26

how do you convert from binary to hexadecimal?

Answer 26

1) convert it into a denary value

2) then convert that into hexadecimal

Question 27

convert 10101101 to denary

Answer 27

128 64 32 16 8 4 2 1
1 0 1 0 1 1 0 1

and so… 173

Question 28

convert 11000101

into hexadecimal

Answer 28

denary - 197

hexadecimal - C5

Question 29

how does lossless compression compress data?

Answer 29

looks for repeating patterns and compresses data

Question 30

how do you calculate the total number of bits needed to store a piece of data compressed using huffman’s coding?

Answer 30

number of bits (for one character) x frequency

ie. if code is 0101 = 4 bits needed
ie. if letter appears 5 times

then total number of bits = 20

• add all the letters together

Question 31

how do you calculate the number of bits needed to store an uncompressed data in ASCII?

Answer 31

7 * total frequency

7 because ASCII needs 7 bits to store data

Question 32

how do you calculate the number of bits saved when compressing a piece of data using huffman’s coding?

Answer 32

uncompressed - compressed = ANS

ANS / uncompressed

Question 33

represent 0000011100000011 in RLE

Answer 33

5 0 3 1 6 0 2 1