Statistics Data collection

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data collection

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23 Terms

1
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Define ‘raw data’
Unprocessed. Just been collected. Needs to be ordered, grouped, rounded, cleaned
2
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d

define qualitative data
Non-numerical, descriptive data
3
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give an example of qualitative data
eye colour, hair colour, gender
4
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define quantative data
Numerical data. Can be measured with numbers, easier to analyse.
5
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give an example of quantative data
height, weight, exam marks
6
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define discrete data
only takes particular values
7
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give examples of discrete data
shoe size, number of people
8
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define continuous data
can take any value
9
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give examples of continuous data
height, weight
10
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define categorical data
data that can be sorted in non-overlapping categories
11
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give an example of categorical data
gender
12
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define ordinal (ranked) data
quantative data that can be given an order or ranked on a rating scale
13
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give an example of ordinal data
marks on an exam
14
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define bivariate data
involves measuring 2 variables
15
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define multivariate data
made up of more than 2 variables
16
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define primary data
data that youve collected yourself, or data collected by someone else for the purpose of your investigation
17
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give an example of primary data
surveys
18
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define secondary data
data already in existence/data collected by others (not for the purpose of your investigation)
19
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give an example of secondary data
wikipedia
20
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list 3 advantages of primary data
\-specific info

\-You do things the way you like it

\-can learn new things

\-data can be outdated
21
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list 3 disadvantages of primary data
* can be a lot of work
* tiring
* expensive
22
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list 3 advantages of secondary data
\-reliable info from real organisations

\-simple,easy

\-can save time and money
23
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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