METHOD GUIDE
Spearman Correlation in SPSS
Monotonic Patterns, Ties and Ordinal Data
A rank-based coefficient asks a different question from a straight-line one, and ties and short rating scales change how it is read. Whether ranks suit the data is settled from the scale and the plot, before rho and its interval are reported.
IN SHORT
What Rank Correlation Measures and When It Fits
Spearman’s rank correlation measures the strength and direction of a monotonic association between two variables by correlating their ranks, which suits ordinal measures and continuous ones whose relationship rises or falls without being a straight line. It says nothing about medians or causes. To run Spearman correlation in SPSS, open Analyze, Correlate, Bivariate, tick Spearman under Correlation Coefficients, and look at a plot of the pair first to confirm that the relationship is monotonic. OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research, carries out and reviews this analysis through an in-house PhD-level statistician.
ANALYSIS SUPPORT
Analysis Support for This Method
Rank correlations are often applied to survey items, where the larger question is how the scale itself should be analyzed. Support for both questions starts from the measurement, not from the coefficient.
Correlation Analysis (Pearson & Spearman)
Association between your variables analyzed within your study design, with the choice of coefficient, the treatment of ties and the reporting settled for your data.
Likert Scale Analysis
The analysis of rating-scale items and summed scales, for when the variables are survey responses and the question is how to treat ordinal data at item and scale level.
BEFORE YOU RUN IT
Checks That Decide Whether Ranks Are the Right Basis
Choosing a rank coefficient because a variable looks skewed is a weak reason, and these four checks give better ones.
Ordinal or Monotonic The measures are ordinal, or the relationship rises or falls steadily without being a straight line. A U-shaped pattern is not monotonic, and a rank coefficient can miss it entirely.
Many Ties Rank correlation ties in SPSS are resolved by average ranks, but when ties dominate, as on short rating scales, a coefficient built for ties, such as Kendall's tau-b, may describe the association better.
Extreme Values Ranks limit the pull of an extreme value but do not remove it. In a small sample a few points at the extremes can still move the coefficient, so their effect is examined and stated.
Sample Size and the p-Value With very small samples the approximate p-value for rho can be inaccurate. The coefficient is reported with its N and an interval, and the conclusion is worded to match the precision.
IN SPSS
How to Run Spearman Correlation in SPSS
Spearman's rho shares the Bivariate dialog with Pearson's r in IBM SPSS, so the steps below keep the two apart. Labels and options differ between versions.
- Check the measurement level of each variable in Variable View, and plot the pair to see whether the pattern is monotonic.
- Open Analyze, Correlate, Bivariate, and move both variables into the list.
- Tick Spearman under Correlation Coefficients, and untick Pearson if it is not part of the plan.
- Keep the test two-tailed unless a one-sided hypothesis was stated in advance, and decide under Options how missing values are excluded.
- Run it and read the Nonparametric Correlations table, noting the N for each pair.
- Add an interval through Confidence interval where your version offers it or, otherwise, Bootstrap where your license includes it.
READING THE OUTPUT
Reading the Nonparametric Correlations Table and What Ties Do to It
Spearman's rho in SPSS is printed in a table headed Nonparametric Correlations, and the ties and the N behind each coefficient decide how far to trust it.
| Output element | What it tells you | What to check |
|---|---|---|
| Nonparametric Correlations (table title) | A matrix of rank-based coefficients for each pair, with Kendall’s tau_b above it when requested | That the coefficient quoted is the one in the row labeled Spearman’s rho |
| Correlation Coefficient | Spearman’s rho, from -1 to 1, which is the Pearson coefficient computed on the ranks | That the sign is described as the direction of a monotonic trend, not a straight-line slope |
| Sig. (2-tailed) | The p-value for the hypothesis of no monotonic association in the population | That it is read as evidence of association, not of its size, and that a small N is flagged |
| N | The number of cases with both values present | That the N of each pair is reported, because pairwise exclusion can change it between cells |
| Kendall’s tau_b (if requested) | A concordance-based coefficient with an adjustment for ties | That it is reported as its own measure, since its values are usually smaller than rho for the same data |
| Bootstrap rows (if requested) | Bias, standard error and an interval for the coefficient | That the interval type, the number of samples and the seed are recorded |
| Scatterplot of the ranks (made separately) | Whether the ranked data rise or fall steadily | That the shape is monotonic before rho is interpreted |
REPORTING
Writing Up Rho, Its Ties and Its Interval
Rho is named as a rank coefficient, and the handling of ties is reported beside it rather than left for a reviewer to ask about.
Write rs(___) = ___, p = ___, with the degrees of freedom (N minus 2) in the parentheses, the N stated and a 95% CI [___, ___] where one is available. Name it as Spearman’s rank correlation, and describe the direction as a tendency, for example that higher values of one variable went with higher values of the other. Say that tied values received average ranks and, where ties were frequent, roughly how many cases were involved. Where your version offers it, the Confidence interval option of the Bivariate dialog adds an interval, with a choice of variance estimate; otherwise it comes from Bootstrap where your license includes it, or from another program. Include a plot of the data or the ranks, and avoid the vocabulary of slopes and straight lines.
COMMON MISTAKES
Questions Reviewers Ask About a Rank Correlation
The rationale for ranks and the treatment of ties draw most of the questions, with a few about wording that implies a straight-line relationship.
Chosen for Skewness Alone Moving to a rank correlation because a variable looks skewed is a weak rationale. The reason given is the ordinal scale, a monotonic pattern or a demonstrated sensitivity to extreme points.
Monotonicity Not Checked A relationship that rises and then falls gives a rho near zero despite a clear pattern. A plot shows whether the relationship is monotonic before the coefficient is interpreted.
Ties Not Mentioned Rating scales produce many tied values. The write-up says that average ranks were used and whether a tie-adjusted alternative was considered, since the coefficient shifts with the choice.
Linear Language Calling rho a straight-line relationship, or reading it as a slope, misdescribes what ranks measure. The text speaks of a tendency for one variable to rise or fall with the other.
Single Item Overread Reporting rho for one 5-point item as though the points were equally spaced overreads the item. The coefficient shows ordering, and the discussion stays within that.
Small Sample, Firm Claim With few cases a large rho can arise by chance, and the approximate p-value can be inaccurate. The interval is wide, and the conclusion is worded to match.
Coefficients already calculated? Independent Statistical Review checks the choice of rank coefficient, the tie handling and the reported interval before you submit.
FREQUENTLY ASKED QUESTIONS
Questions About Spearman's Rho Output
Rho against Pearson's r on ranks, tau-b for tied data and a p-value that differs between programs open this set.
Is Spearman's rho the same as Pearson's r computed on the ranks?
In value, yes: rho equals the Pearson coefficient calculated on the ranked data, with tied values given average ranks. The difference lies in the question. Rho describes a monotonic trend, not a straight line, and it does not require the raw scores to follow a bivariate normal distribution. It still assumes independent pairs and a relationship that does not change direction.
Should I report Spearman's rho or Kendall's tau-b when I have many ties?
Both handle ties, but they measure different things, so one is chosen before the results are seen and named in the report. Tau-b is based on pairs of cases ordered in the same or in opposite directions, and its values are usually smaller than rho for the same data. It is often considered for small samples with many ties, while rho remains the more familiar choice.
Why can the p-value for my rho differ from another program's?
The Sig. (2-tailed) value in SPSS comes from an approximation, while some other programs compute the p-value from the exact permutation distribution for small samples without ties. The two can differ noticeably when N is small, and neither changes the coefficient itself. Report which was used, and treat a result near the threshold in a small sample with caution.
Can OnlineSPSS check which rank coefficient fits my data?
Yes. An in-house PhD-level statistician can look at the measurement scale, the ties and the shape of the relationship, choose and justify the coefficient, and carry out the analysis or review one you have run. Where only the write-up remains, Results Reporting & Interpretation covers that stage. The interpretation and the conclusions remain with you.
How do you protect my research data and confidentiality?
Your data and project details are handled confidentially, and project information is not published. Researcher names and institutions are not used publicly without permission. An NDA is available where required and can be arranged before sensitive materials are shared. Read more about confidentiality and data security.
What happens when I request an assessment, and how long does it take?
You share your research question, design and relevant materials, such as the dataset or the output you have, and a statistically trained Research Coordinator reviews the request and responds the same day. The analysis, deliverables, timeline and one fixed project fee are then confirmed before any work begins, so the timeline follows from the agreed scope.
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NEXT STEP
Ordinal Variables and
a Coefficient to Justify?
Include the variables with their scales, a note on how many tied values you expect and any output so far. With those in hand, the choice between rho and tau-b and the way ties are reported can be agreed as part of the scope.
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