Spearman's rank correlation coefficient

Question 1

why is this techniques used?

Answer 1

to measure the strengths of a relationship between two variables resulting in a positive or negative correlation

Question 2

benefits of stats tests

Answer 2

assess the degree of correlation allowing for further statistical analysis
visual representation via scattergraph
significance tests validate data set

Question 3

limitations of stats test

Answer 3

needs between 10-30 data sets fore reliable comparison

Question 4

where can this data be presented

Answer 4

on scattergraphs

Question 5

what relationships will be shown relating to the scattergraphs

Answer 5

closer to 1 is strong positive correlation
closer to -1 is a strong negative correlation
result of 0 is no relationship

Question 6

how to calculate

Answer 6

1. rank data sets, highest ranked as one
2. calculate the difference between the ranks
3. square the difference
4. add up the total of squared differences
5. put values into the formula
6. minus answer from 1 to get spearmint rank

Question 7

what do you do when ranking and there are too numbers the same
ex rank 3 and rank 4

Answer 7

add the two together: 3+4 = 7
divide by 2 = 3.5
each rank them is 3.5
from here replace as many ranks that are the same with 3.5 and skip 4
on your rank you would have 3.5 x2 instead of 3 and 4

Question 8

in a positive correlation what happens to values

Answer 8

both go up

Question 9

in a negative correlation what happened to figures

Answer 9

one goes up and one goes down

Question 10

calculate degrees of freedom

Answer 10

number of pairs minus 2

n-2

Question 11

degrees of freedom on significance table/ graph

Answer 11

the ‘n’ used to correlate what the percentage of significance is