types of data

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14 Terms

1
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nominal data is also referred to as

categorical data

2
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nominal data defintion

  • where numbers usually refer to people in categories

  • how frequently something occurs

3
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example of nominal data

how many people are right handed and left handed

4
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appropriate descriptive statistics for nominal data

  • percentage

  • ratio

  • pie chart

  • bar chart

5
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ordinal data defintion

  • where the scores obtained are on a numerical scale

  • can be out in rank order

  • however the units of measurement are not of equal, definable size

  • usually based on opinion so tend to be subjective rather than objective

6
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appropriate descriptive statistics for ordinal data

  • mean

  • mode

  • ratio

  • percentage

  • line graph

  • histogram

  • pie chart

7
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interval data defintion

  • data is on a numerical scale with unit of equal, definable data

  • data is objective e.g. reaction time, height

8
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appropriate descriptive statistics for interval data

  • mean

  • median

  • mode

9
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strengths of nominal data

  • easy to generate from closed questions, so large amount of data collected increasing reliability

  • quick to find mode to assess central tendency

10
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weaknesses of nominal data

  • without linear scale ppts are unable to express degrees of response

  • can only use mode as a measure of spread, no median and mean

11
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strengths of ordinal data

  • more informative rather than nominal data

  • easy to generate from likert and rating scales

  • median can be used as on linear scale, as well as mode

12
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weaknesses of ordinal data

  • gaps between the groups are only relative - so comparisons may be invalid as ppts may interpret the scale differently

  • gaps between groups are not equal so a mean cannot be used to assess central tendency

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strengths of interval data

  • more informative - points are directly comparable because they are equal

  • easy to generate from closed questions

  • scientific measurement - highly reliable

14
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weaknesses of interval data

  • in interval scales that are not scientific measures there is no absolute baseline

  • this means scoring zero may not mean the ppt does not demonstrate that variable at all, merely may mean than the scale does not measure it