Spearman Rank vs Pearson Correlation Coefficient - (Aug/09/2013 )
I have observational data and want to do a correlation test to determine the relationship.
For one variable I have a hygiene scoring of dairy cattle of various farms, so this data is obviously non parametric and ordinal since I ranked the cows from 1-4
For the other variable I have TPC (total plate count x1000 CFU/mL) of the bulk milk tank for that farm during the period I scored the cattle. So this data is parametric and interval or ratio.
Question - do I still use the Spearman Rank Correlation Coefficient to analyze my data? I'm just confused since one data set is non parametric and the other is parametric.
what you should look at is the distribution of the data i.e. if they have e.g. a normal distribution or not. As at least the TPC are count data it would be more a Poisson distribution which would need e.g. a non-parametric test method (or any other test that can deal with this distribution). So I'd go with Spearman's Rank Correlation Coefficient as it's a non-parametric method also for discrete variables whereas Pearson's correlation coeff. needs at least one normal distributed variable and tests only a linear correlation if my memory is right.
Thanks for your response - I went ahead and did a Spearman Rank Correlation Coefficient test instead of a Pearson in order to decrease my type I error, so I treated all the data sets as non parametric.
You can also use Kruskall-Wallis test (it is non-parametric 1-way ANOVA) if you have grouped data by hygiene scoring