Chapter Three - Data Representation

Question 1

Data vs. Information?

Answer 1

• data: facts, values
• information: data that is organized so that it is USEFUL
• e.g. phone records; getting the evidence you need from the phone records;

Question 2

Data compression?

Answer 2

• REDUCING SPACE needed to STORE DATA

Question 3

Bandwidth?

Answer 3

• # of BITS/BYTES that can be TRANSMITTED from ONE PLACE to ANOTHER in GIVEN AMOUNT of TIME.
• kind like the speed limit/traffic congestion

Question 4

Compression ratio?

Answer 4

• SIZE of COMPRESSED DATA/SIZE of UNCOMPRESSED DATA;

e. g. compressing an image 2mb/8mb = .25

Question 5

Lossless vs. Lossy?

Answer 5

• Lossless: no loss of info

- Lossy: loss

Question 6

Analog vs. Digital?

Answer 6

• analog: CONTINUOUS representation of data (e.g. mercury thermometer)
• digital: DISCRETE representation of data (computers)

Question 7

Digitize?

Answer 7

• act of BREAKING INFORMATION DOWN into DISCRETE PIECES (e.g. taking photo with digital camera)

Question 8

Pulse-code modulation?

Answer 8

• digital signals that jump sharply between TWO EXTREMES (e.g. phone -> electronic signals transferring binary data)&raquo_space; can degrade but information isn’t lost; when signal is too weak, RECLOCK.

Question 9

Reclock?

Answer 9

• REASSERTING an original DIGITAL signal before it becomes TOO DEGRADED.

Question 10

Signed-magnitude representation?

Answer 10

• used in GRADE SCHOOL;
• sign (+/-) represents the ordering of the number and value represents the magnitude (visualize the linear graph w/ 0 in the middle)

Question 11

Ten’s complement?

Answer 11

• representation of NEGATIVE numbers where it is raised to 10 (or something…will watch Khan’s youtube video)

Question 12

Overflow?

Answer 12

• situation where value CANNOT FIT in # of digits reserved for it. (not enough bits; e.g. 8 bits -> 257)

Question 13

Radix point?

Answer 13

• DOT that separates WHOLE PART from FRACTIONAL PART; (decimal point in base other than 10)

Question 14

Floating point?

Answer 14

• how values are represented in computer;

|&raquo_space; (e.g. -15,500)keeps track of SIGN (+/-), MANTISSA (155), and EXPONENT(10^2);

Question 15

Scientific notation?

Answer 15

• You know what this is»12001.3 = 1.20013E+4 Form of floating point representation.

Question 16

Character set?

Answer 16

• LIST of characters and CODES used to represent each one (e.g. ASCII & Unicode)

Question 17

Keyword encoding?

Answer 17

• replacing a frequently used WORD with a single character (e.g. as = ^; must = &); compression ratio approx .9

Question 18

Run-length encoding?

Answer 18

• replacing long series of REPEATED CHARACTERS with aCOUNT of the repetition&raquo_space; DNA sequences;
• e.g. AAAAAAA&raquo_space; *7A; compression ratio approx .7

Question 19

Huffman encoding?

Answer 19

• VARIABLE-LENGTH BINARY STRING to represent frequently used character; e.g. A > 00; D&raquo_space; 1011 (like scrabble!) compression ratio approx .4

Question 20

Vector graphics?

Answer 20

• image representation in terms of LINES & SHAPES

Question 21

Video codec?

Answer 21

• methods used to SHRINK the size of a video (almost all are lossy); uses temporal and spatial compression.

Question 22

Temporal compression?

Answer 22

• compression based on DIFFERENCE between consecutive FRAMES (if no change b/w frames, doesn’t waste space by duplicating same information)

Question 23

Spatial compression?

Answer 23

• groups PIXELS into BLOCKS that have the SAME COLOR (e.g. portion of blue sky)