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Analysing deprivation. Statistical analysis Spearman’s Rank Correlation Coefficient Gives a numerical value to the trend on a scatter graph.

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Presentation on theme: "Analysing deprivation. Statistical analysis Spearman’s Rank Correlation Coefficient Gives a numerical value to the trend on a scatter graph."— Presentation transcript:

1 Analysing deprivation

2 Statistical analysis Spearman’s Rank Correlation Coefficient Gives a numerical value to the trend on a scatter graph

3 You need data Choose 10 boroughs of London Choose 3 indicators Using London borough Stat-Pack collect the dataUsing London borough Stat-Pack collect the data

4 Spearman’s rank: how to BoroughData 1RankData 2RankDifferenc e between ranks Differenc e squared BoroughGCSE results RankHomeles s RankDifferenc e between ranks Differenc e squared What would be the hypothetical relationship between the two?

5 Hypothesis – the higher the GCSE results the lower the number of homeless BoroughGCSE results RankHomeles s RankDifferenc e between ranks Differenc e squared City110981

6 BoroughData 1RankData 2RankDifferenc e Diff sq Total Diff sq =

7 Spearman’s rank formula Coefficient = 1- 6(∑d²) n³-n Where (∑d²) is the total of the differences squared Where n is the number of data sets (in this case 10 – so n³-n = 990

8 What does your result mean? The coefficient (R) is a value between -1 and +1 Closer to +1 you get the stronger a positive relationship there is Closer to -1 you get the stronger a negative relationship there is (Remember – the hypothesis) Hypothesis – the higher the GCSE results the lower the number of homeless

9 Graphically

10 Over to you – run the numbers! Comment on your results Offer any reasons for your results


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