spearmans rank correlation coefficient?

Question

plz tell me if you have either:
1. never heard of it
or
2. heard of it
or
3. can do it
or
4. hav attempted it

just answer even if u havnt heard of it, im interested

Answer 1

3. Can do it (given the formula)

Answer 2

In statistics, Spearman's rank correlation coefficient, named after Charles Spearman and often denoted by the Greek letter ρ (rho), is a non-parametric measure of correlation – that is, it assesses how well an arbitrary monotonic function could describe the relationship between two variables, without making any assumptions about the frequency distribution of the variables. Unlike the Pearson product-moment correlation coefficient, it does not require the assumption that the relationship between the variables is linear, nor does it require the variables to be measured on interval scales; it can be used for variables measured at the ordinal level.

In principle, ρ is simply a special case of the Pearson product-moment coefficient in which the data are converted to ranks before calculating the coefficient. In practice, however, a simpler procedure is normally used to calculate ρ. The raw scores are converted to ranks, and the differences d between the ranks of each observation on the two variables are calculated.

A generalisation of the Spearman coefficient is useful in the situation where there are three or more conditions, a number of subjects are all observed in each of them, and we predict that the observations will have a particular order. For example, a number of subjects might each be given three trials at the same task, and we predict that performance will improve from trial to trial.

Answer 3

Have done it many times; especially in class where I taught MBA stat.

Fundamentally the Spearman rank correlation rates how tightly one ordered list of data (sorted ascending or descending) correlates to another ordered list of data. For example, if you do a Spearman on two lists, each of exactly the same numbers, the correlation would be 1.0, which means there is no variance between the two sets of data.

There are equations to manually do the Spearman, but in this day and age of computers, why bother? Excel has a function that can be used to do the correlation on two arrays of data on the spreadsheet.

Answer 4

I did some statistics courses as part of an economics degree and worked with "correlation coefficients", but never heard the use of the term "spearsman rank". I have some versatile books on stats though; could look something up for you.

Answer 5

PMCC finds out how close to sets of points lie to a straight line or line of best fit. Spearman's rank finds out how closely two sets of points agree with each other. It's a similar thing but it can produce completley different answers. :))

Answer 6

It is quite well known and I prefer it. It is a non parametric test and can be used in all circumstances, even when the assumptions required by the Pearson product moment corr. coef. are not justified.
It is much easier to calculate than the Pearson coef. and so it was more popular in older days when computer programmes and scientific calculators were not available.

For more than about 12 pairs of results, the same tables can be used to test its significance, as for the Pearson coef.

Answer 7

Yep, did it in geography at school, and it's super-simple way to work out whether two populations are related at all. All you need to do is put the data into order, sum the ranks, then plug numbers into the equation, which is a pretty quick job, unless it's a huge dataset.

Answer 8

Yes I have heard of it and done it. It is a nonparametric way to estimate the population correlation. I should probably be used when the data has outliers.

Answer 9

Heard of it and have used in in statisitcal analysis for maths and biology