Spearman Correlation

Question 1

When do we use spearman’s for correlation?

Answer 1

• ordinal data
• residuals are not normally disturbed
• relationship is non-linear

Question 2

What does Spearman correlation do?

Answer 2

calculates the relationship based on the rank order of the data, rather than actual values

Question 3

What are the steps of Spearman’s test?

Answer 3

1. Rank the scores for each variable separately
2. Calculate the differences between ranked pairs
3. Square the differences
4. Sum the squad differences
5. Compute the Spearman rank-order correlation coefficient

Question 3

What do you do if there is two of the same score?

Answer 3

Give the average, e.g. if 3rd and 4th then they both would be 3.5

Question 4

What is Spearman’s rank correlation coefficient?

Answer 4

r

Question 5

What is a dependent correlation?

Answer 5

Two correlations that share a common variable and come from the same sample of ppts,

Question 6

What are independent correlations?

Answer 6

same variables, different groups

Question 7

What is spearmans coefficient (number)

Answer 7

0.5

Question 8

A psychologist is studying the relationship between sleep duration and reaction time in 6 participants. After ranking both variables, the sum of squared differences (∑ d²) is found to be 0.

Based on the Spearman rank correlation formula, what does this indicate about the relationship between sleep duration and reaction time?

Answer 8

The two variables are perfectly correlated.

Question 9

What is the key difference between independent and dependent correlations?

Answer 9

Independent correlations involve correlations between unrelated variables, while dependent correlations involve correlations that share a common variable

Question 10

A psychologist measured the correlation between daily caffeine consumption (mg) and productivity scores and found:

r(38) = .12, p = .48, 95% CI [-.18, .40].

Which of the following best represents the correct APA-style interpretation of this result?

Answer 10

There was no statistically significant correlation between caffeine consumption and productivity, r(38) = .12, p = .48, 95% CI [-.18, .40].

Question 11

Suppose you are given the following values:

Covariance cov(x,y) = 50.3

Standard deviation Sx = 5.1

Standard deviation Sy =10.8

What is the correlation coefficient r(x,y) ?

Answer 11

0.91

Question 12

Researchers examined data from 120 cities to understand how green space, air pollution, and happiness are related.

There was a strong negative correlation between green space and air pollution, r(118) = -.76, p < .001, and a strong positive correlation between green space and happiness, r(118) = .66, p < .001.

A comparison of these two dependent correlations using Fisher’s Z transformation test indicated that the difference between them was statistically significant, z = 10.65, p < .001.

What conclusion best fits this result?

Answer 12

The two correlations differ significantly in strength, with the relationship between green space and air pollution being stronger in magnitude.