The Difference Between Pearson’s Correlation and Spearman’s Rank Correlation

In quantitative research, one of the most common questions is whether two variables are related, and if so, how stronglythey are associated. Two popular statistical methods used for this purpose are the Pearson’s Correlation Coefficient (r) and the Spearman’s Rank Correlation Coefficient (ρ or rs).

Both techniques measure the relationship between two variables, but they differ in their assumptions, data requirements, and types of relationships they can detect.

The Difference Between Pearson’s Correlation and Spearman’s Rank Correlation

What Is Pearson’s Correlation?

The Pearson’s Correlation Coefficient (r) is a parametric statistic that measures the linear relationship between two quantitative variables.The coefficient ranges from -1 to +1:

• +1 indicates a perfect positive linear relationship (as one variable increases, so does the other).

• -1 indicates a perfect negative linear relationship (as one variable increases, the other decreases).

• 0 indicates no linear relationship.

Key Assumptions

1. Both variables are measured on an interval or ratio scale.

2. The relationship between variables is linear.

3. The data are normally distributed.

4. There are no significant outliers that distort the relationship.

Example

Research Topic: “The Relationship Between Study Hours and Exam Scores Among University Students”

• Independent Variable: Number of study hours (hours)

• Dependent Variable: Exam scores (points)

If both variables are continuous and normally distributed, the Pearson’s Correlation is appropriate to determine whether more study hours are associated with higher exam scores.

What Is Spearman’s Rank Correlation?

The Spearman’s Rank Correlation Coefficient (ρ or rs) is a non-parametric statistic that measures the monotonic relationship between two variables based on their ranked values, not their raw scores.

It is useful when the data do not meet parametric assumptions, such as normal distribution, or when there are outliersthat may distort the Pearson correlation result.

Example

Research Topic: “The Relationship Between Stress Level and Work Performance Among Employees”

• Independent Variable: Stress level (1 = low, 5 = high)

• Dependent Variable: Work performance (supervisor rating 1–5)

Since the data are ordinal (ranked) and not normally distributed, the Spearman’s Correlation is more appropriate than Pearson’s for assessing the relationship.

How to Choose Between Pearson’s and Spearman’s Correlation

The choice depends mainly on the nature of the data and the type of relationship expected.

• Use Pearson’s Correlation when both variables are continuous, normally distributed, and have a linear relationship.

• Use Spearman’s Correlation when the data are ordinal, non-normally distributed, or contain outliers.

• If you expect a general trend (monotonic relationship) rather than a strictly linear one, the Spearman’s Correlationis the better choice.

In summary:

Pearson’s Correlation is suitable for continuous, normally distributed data with linear relationships.Spearman’s Correlation is suitable for ranked or non-normally distributed data, or data with outliers.

Why You Should Use Data Investigator

Choosing the right correlation test requires more than just knowing the formulas — it demands a deep understanding of data characteristics, measurement scales, and statistical assumptions.Using the wrong method may lead to inaccurate interpretations and misleading conclusions.

With over 15 years of experience in SPSS-based data analysis, Data Investigator provides expert guidance in selecting the right statistical methods, ensuring accurate results and clear interpretation for academic, business, and medical research.

Our Services Include

• Conducting correlation and regression analysis using SPSS

• Checking data assumptions and distribution before selecting methods

• Applying Pearson’s or Spearman’s Correlation accurately

• Providing detailed interpretations of results in plain, academic language

• Issuing official Certificates of Statistical Analysis

Whether you are a thesis student, medical researcher, or government organization,Data Investigator is your trusted partner for accurate, reliable, and professional correlation analysis.

For more information:

E-mail: info@datainvestigatorth.com

Line: @datainvestigator