Summarising data

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Last updated 11:46 AM on 9/4/25
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19 Terms

1
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What types of data can be presented in various ways?

  • Qualitative and quantitative data can be presented using tables, graphs, or verbal summaries

2
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What is qualitative data?

  • non-numerical data collected from methods like interviews, observations, or open-ended surveys

3
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What is quantitative data?

  • numerical data that can be analysed statistically and summarised using tables and graphs

4
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Why are tables useful in summarising quantitative data?

  • they clearly present data and show patterns or raw scores before analysis

5
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What are descriptive statistics?

  • summaries such as the mean, range, and standard deviation used to describe data sets

6
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What kind of data is shown in bar charts?

  • non continuous (categorical) data

7
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Why must the bars in a bar chart not touch each other?

  • because the data is discrete (separate categories) and not continuous

8
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What kind of data is shown in line graphs?

  • continuous data, where values are measured along a scale

9
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What are line graphs good for?

  • showing plotted data over time or comparing multiple data sets on the same axes

10
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What kind of data is shown in histograms?

  • continuous data, grouped into intervals (like time taken, height, or age)

11
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How do histograms differ from bar charts?

  • histogram bars touch (continuous data); bar chart bars don't (discrete data)

12
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What does the height of a column in a histogram represent?

  • the frequency (number of values) in that interval

13
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What kind of data is shown in scattergrams?

  • two continuous variables plotted to show a possible correlation

14
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What can scattergrams show?

  • whether two variables are related, positively, negatively, or not at all

15
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What is plotted on a scattergram?

  • one variable on the x-axis, the other on the y-axis

16
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Why must you not draw a line in scattergrams?

  • you should draw a line of best fit only if a clear trend is visible to summarise the relationship

17
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What is raw data?

  • unprocessed scores collected before any statistical analysis

18
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How do you calculate a percentage from a table?

  • divide the part by the whole and multiply by 100 (e.g. 36/60 × 100)

19
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What should you always include when plotting a graph?

  • labels for axes (including units), title, and accurate plotting

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