Spearman's rank-order correlation is the non-parametric alternative to Pearson's: it measures the strength and direction of a monotonic relationship using ranks, so it works for ordinal data or when a relationship is not linear. The APA 7 write-up is short but uses a different symbol, and people often mix it up with Pearson. This guide gives you the exact format, a worked example you can copy, and the mistakes reviewers catch.
What you need before you write a single word
An APA 7 write-up of a Spearman correlation needs these values from your output:
- Spearman's rho, reported with the symbol r_s (an italic r with a subscript s).
- The degrees of freedom (df), which is N minus 2, or simply report N.
- The exact p value.
Like Pearson's r, r_s is itself the effect size, so no separate one is needed.
The APA 7 format template
Report the result in running text using this pattern:
There was a [strong/moderate/weak] positive/negative monotonic correlation between [variable 1] and [variable 2], r_s(df) = .XX, p = .XXX.
Formatting rules reviewers actually check:
- Use the symbol r_s (italic r, subscript s), not plain r, so the reader knows it is Spearman.
- Put the degrees of freedom (N minus 2) in parentheses, or report N in the sentence.
- No leading zero on r_s or p, because neither can exceed 1, so write r_s = .52, not 0.52.
- Round r_s to two decimals. Report p to two or three decimals, and if it is below .001, write p < .001.
- Describe the relationship as monotonic, not linear.
A worked example
Suppose you correlated a satisfaction rating (1 to 7, ordinal) with years of membership for 45 customers.
- N = 45, so df = 43
- Result: r_s(43) = .52, p < .001
Written up in APA 7, that becomes:
There was a moderate positive monotonic correlation between years of membership and satisfaction rating, r_s(43) = .52, p < .001. Customers with longer memberships tended to report higher satisfaction.
The sentence carries the direction, the strength in words and as a coefficient, and the significance.
Mistakes reviewers catch
- Using the Pearson symbol. Report Spearman as r_s, not r, so the reader knows which correlation you ran.
- Calling the relationship linear. Spearman measures a monotonic relationship (consistently increasing or decreasing), which need not be a straight line.
- A leading zero on r_s or p. APA drops it for values bounded by 1.
- Claiming causation. A correlation is an association, not evidence that one variable causes the other.
- Choosing Spearman by default. If both variables are continuous and the relationship is linear with no serious outliers, Pearson is usually the better choice. See our guide on reporting a Pearson correlation.
- Writing p = .000. Report p < .001.
When to use Spearman instead of Pearson
Use Spearman's correlation when:
- One or both variables are ordinal (ranks or Likert-type ratings), or
- The relationship is monotonic but not linear, or
- There are outliers that would distort Pearson's r, since ranks are robust to extreme values.
Let KyroStat do the write-up for you
Getting the symbol and the leading-zero rules right is where errors creep in. KyroStat runs the Spearman correlation on your data, produces the scatterplot, and hands you the finished APA 7 sentence with the correct r_s notation and the underlying Python or R code. Upload your spreadsheet, and the report is done in seconds.
Frequently asked questions
What symbol do I use for a Spearman correlation? r_s, an italic r with a subscript s. Some journals also accept the Greek letter rho.
What degrees of freedom does Spearman use? N minus 2, the same as Pearson. With 45 cases, df = 43.
Is Spearman an effect size on its own? Yes. Like Pearson's r, the coefficient itself is the effect size; .10 is small, .30 is medium, .50 is large.
My p value shows as .000. What do I write? Report p < .001. A p value is never exactly zero.