# Statistics Data collection

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Define ‘raw data’

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## Tags and Description

data collection

### 23 Terms

1

Define ‘raw data’

Unprocessed. Just been collected. Needs to be ordered, grouped, rounded, cleaned

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2

d

define qualitative data

Non-numerical, descriptive data

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3

give an example of qualitative data

eye colour, hair colour, gender

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4

define quantative data

Numerical data. Can be measured with numbers, easier to analyse.

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5

give an example of quantative data

height, weight, exam marks

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6

define discrete data

only takes particular values

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7

give examples of discrete data

shoe size, number of people

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8

define continuous data

can take any value

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9

give examples of continuous data

height, weight

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10

define categorical data

data that can be sorted in non-overlapping categories

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11

give an example of categorical data

gender

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12

define ordinal (ranked) data

quantative data that can be given an order or ranked on a rating scale

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13

give an example of ordinal data

marks on an exam

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14

define bivariate data

involves measuring 2 variables

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15

define multivariate data

made up of more than 2 variables

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16

define primary data

data that youve collected yourself, or data collected by someone else for the purpose of your investigation

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17

give an example of primary data

surveys

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18

define secondary data

data already in existence/data collected by others (not for the purpose of your investigation)

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19

give an example of secondary data

wikipedia

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20

list 3 advantages of primary data

-specific info

-You do things the way you like it

-can learn new things

-data can be outdated

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21

list 3 disadvantages of primary data

• can be a lot of work

• tiring

• expensive

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22

list 3 advantages of secondary data

-reliable info from real organisations

-simple,easy

-can save time and money

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23

list 3 disadvantages of secondary data

-info not done the way you like it

-info might be outdated

-data might not suit your specific needs

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