How to count Spearman Rank order correlation

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SUMMARY

The discussion focuses on calculating the Spearman Rank Order Correlation for two sets of data using the formula provided by VassarStats. The user successfully computed the correlation coefficient as approximately -0.93 using the ranks from the website but encountered difficulties in understanding the calculation process. The final calculation yielded a different result of approximately -0.90, leading to confusion about the correct methodology. The discussion highlights the importance of mastering the Spearman correlation formula and its application in statistical analysis.

PREREQUISITES
  • Understanding of Spearman Rank Order Correlation
  • Familiarity with statistical formulas and calculations
  • Basic knowledge of rank assignment in datasets
  • Experience using online statistical tools like VassarStats
NEXT STEPS
  • Review the Spearman Rank Order Correlation formula and its derivation
  • Practice rank calculations with different datasets
  • Explore alternative statistical tools for correlation analysis
  • Study the implications of negative correlation in data interpretation
USEFUL FOR

Students preparing for statistics exams, data analysts, and anyone seeking to understand rank correlation methods in statistical analysis.

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Homework Statement


calculate the rank order correlation between the following data:

6, 5, 4, 2, 3, 3, 8, 3, 7, 6, 7, 5, 5, 4, 2, 7, 6, 2, 4, 6

4, 3, 6, 7, 6, 7, 1, 9, 1, 2, 3, 4, 5, 5, 7, 1, 2, 9, 5, 4


Homework Equations



Following the output from http://www.vassarstats.net/corr_rank.html, given the ranks, then from each individual rank subtract the equivalent opposing / matching rank. Lastly, raise every subtraction to the power of two and sum up results:

Ʃ( #x_{i} - #y_{i} )^{2}

The Attempt at a Solution



I have used the aforementioned online site to help my calculations, and have used the ranks given there, from the appropriate variables, to perform the previously described actions.

The answer is ≈ -0.93. This is confirmed by vassarstat.net. However, vassarstat does not give any explanation how to perform the rest of the problem.

I can only get ≈-0.90. After Ʃ( #x_{i} - #y_{i} )^{2}, I get 2529. Then I use the spearman rank order correlation equation 1 - \frac{6 * 2529}{20 * (20^{2} - 1)} ≈ -0.90
 
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Anyone? Exams are just behind the corner and I can not figure this one out. Hate it if they would ask to use this in the test. It could be so simple if i could just understand
 

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