Encoding data Flashcards Preview

ICT A-level > Encoding data > Flashcards

Flashcards in Encoding data Deck (11):
1

What is encoding data?

Encoded data is data replaced with short codes.
Example: Male/Female as M/F
Red/Green/Blue as R/G/F

2

What do we call a way of encoding an opinion?

A value judgement.

3

What are the different data types?

- Boolean
- Integer
- Real
- Text/string

4

Definition and example of - BOOLEAN (data type)

It can hold one of two values.
Example: Yes/No, True/False, Male/Female, 1/0

5

Definition and example of - INTEGER (data type)

Holds whole numbers.
Example: 1, 2, 3, 4, 5.

6

Definition and example of - REAL (data type)

Holds decimal numbers.
Example: currency, 1.25

7

Definition and example of - TEXT/STRING (data type)

Holds any alphanumeric character, including letters, numbers and symbols.

8

What is a value judgement?

When there is no absolute agreement on the value of a data item. When this happens a value judgement is coded for computer input.
- A value judgement is a matter of opinion rather than fact

9

State an example of a value judgement.

Example: the following data may be collected on a dating agency form - I am: handsome /good looking / average / ugly
With value judgements there may be no single correct value, the value depends on someone's opinion.

10

Advantages of encoding data.

- Takes up less storage space in computers memory, m is one character male is 4 characters
- Less chance of transcription errors because the user is tying fewer characters
- Takes less time to type and is therefore faster to enter data
- Greater consistency of data the user is using a restricted set of values
- Processing is faster because less RAM is required

11

Disadvantages of encoding data.

- The precision of the data may be coarsened as there is a lack of choices.
Example: light brown hair/ brow hair/ dark brown hair may all be classed as brown.
This loss of precision must be weighed against its advantages; clearly a shorter survey will take less time to complete but Is likely to contain coarser data

- No agreement as value judgements depend on opinions.
Example: one person's hot curry may be another person's medium