Population 3.5 - Spearman’S Rank

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Population 3.5 - Spearman’S Rank

  1. 1. Spearman’s Rank Correlation Coefficient A statistical technique to quantify the degree of relationship – correlation – between two sets of data
  2. 2. Stats and Geography <ul><li>You will be required to undertaken statistical analysis for your internal assessment (IA) </li></ul><ul><li>You do not need to be good at Maths to use them effectively </li></ul><ul><li>You must choose an appropriate and relevant technique </li></ul><ul><li>You must be accurate and follow all the steps carefully and methodically </li></ul><ul><li>You must carefully integrate the results of your statistical process into the analysis section of you write-up </li></ul>
  3. 3. Correlation <ul><li>Correlation assess the relationship between 2 sets of data in terms of the degree of similarity between the data sets. </li></ul><ul><li>As one set of values changes (increases for example) what does the other set of values do? </li></ul>
  4. 5. Spearman’s Rank Correlation Coefficient gives a numerical value (a quantity) to the degree of correlation between 2 sets of data
  5. 6. Step 1 <ul><li>Be clear about the hypothesis you are testing and the 2 variables being analysed (e.g. the higher the purchasing power of a country the lower the fertility rate) </li></ul><ul><li>Collect the data you need (a minimum of 10 pairs of values is required i.e you sample size should be 10) </li></ul>
  6. 7. Step 2 – The Table ∑ d 2 Australia Ecuador Taiwan Slovakia France USA China Ethiopia d 2 d Rank Fertility Rate Rank PP (US$) Country
  7. 8. Step 3 – The Formula
  8. 9. Step 4 – Interpret the Results
  9. 10. Step 5 - Test for Significance
  10. 11. Step 6 – Summarize the Results <ul><li>E.g. </li></ul><ul><li>With a Spearman’s Rank value of -0.83 I identified a strong negative correlation between purchasing power and fertility rates. The results were successfully tested for significance at both the 95% and 99% confidence levels thus I can conclude that the results are very reliable and did not occur by chance. These results therefore support the hypothesis that “the higher the purchasing power of a country the lower the fertility rate. The scatter graph of the same data (figure 1) further supports these conclusions. </li></ul><ul><li>These are the results I expected and can largely be explained in terms of levels of development. As a country develops …….. </li></ul>
  11. 12. The Pros – and Cons The Geofile handout (No 511 Jan 2006) – from which a large amount of this information comes – addresses the advantages and disadvantages of Spearman’s Rank. You should be doing the reading.

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