Explaining: Spearman's Rank Correlation Coefficient

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Spearman's rank is probably one of the most useful statistical tests that we can do in Geography to prove a relationship between two different sets of data. In this video I explain how to use it and and what it means. This is ideal for Geography coursework.

Опубликовано:

15 июл 2024

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Комментарии : 15

@GlynisDance Год назад

Thank you - your explanation was completely clear and fresh, even though my brain feels utterly tired!

@patrickwise6297 4 года назад

Thank you - very helpful. Note, though the "14" width should have rank 7 and the "18" width should have rank 6 in the first Sunflower example.

@sergio7470 3 года назад

Thank you for the clear explanation and getting to the point.

@amantaybilash9495 4 года назад

Very good explanations. Thanks for sharing!

@AnnaelleD 4 года назад

Whoua! Great video. Thank you very much.

@hopestreet3452 3 года назад

Really clear explanation - thank you :)

@Dark6In6The6Eyes 3 года назад

Thank you, this was very clear.

@abishrantasaikia2393 3 года назад

Thank you so much. It was very helpful.

@Memzii Год назад

Thank you!

@emmanuelbanda7123 4 года назад

Nice

@tanoysaha9243 4 года назад

Can it be computed for all quantitative variables??

@najlaelhachem9159 4 года назад

Hi, thanks for these explanations. It's is very clear. I have two questions: First, would it be possible to use spearman's rank correlation with different rank numbers (eg: 7 ranks for the height and 10 for the width)?. Second, would it be possible to use the formula by ranking pvalues? Thanks plenty, Najla

@archidar1 4 года назад

1. I dont think that would be well defined. We cant even apply Pearsons correlation to unmatched data. I.e. it doesnt make sense to compare two data sets of different length. An extreme example is to compare 1 data value against no data value (e.g. height 1.7m, weight unknown). 2. Depends on whether the p-values are comparable. Some argue that p-values should only be seen as binary, either being greater than or less than the level of significance, and that the value of p-values should be ignored.

@kimballclark1392 Год назад

When there are repeated values I find a different formula where the D^2 gets terms added for each repeated value a 1/2(value^3 -value). For each value that is repeated a term is added to the numerator. Can you explain why your formula is different?