In my previous post,  it has been considered what is refered to as bivariate correlation invented by Pearson.

This guide will focus on spearman correlation analysis with detailed description.

In the course of this guide , I shall tend to define what spearman Correlation is all about and how to undergo the analysis.

![Screenshot_20220329-063810_1.png](https://images.hive.blog/DQmQ26aVcHKtiMHafxJFb1hodcFpJKGND6RmmK6eWKZ2qGj/Screenshot_20220329-063810_1.png)<center> Taken with smartphone Techno PoP5 </center>


What is spearman correlation?

Spearman correlation is also regarded as correlation of ordinal variables. It was invented by spearman to find the relationship between variables with ranking.

Variables with ranking are also refered to as ordinal variables. Just as Pearson bivariate correlation is measured with its coefficient, spearman coefficient of correlation is measured with rho.

According to  correlation analysis, it is defined by its coefficient explained as thus
.
He analyzed or grouped the result of correlation into three when considering for two variables.

Positive correlation
A positive correlation of two variables, example variable X and variable Y indicates that the higher variable X the higher variable Y.

This doesn't mean variable X is responsible to  cause a change in variable Y. It only means both variables linked together in a process can thus be explained by the coefficient

Example of this correlation can be found in the gross domestic product (GDP) of a country. The more infrastructures are built , refineries and good motorable roads and even agriculture is been taken into consideration, the higher the GDP of that country.

Negative correlation
A negative correlation of two variables, example variable X and variable Y indicates that the higher in value of variable X, the lower in value for variable Y and vice versa.

Example of this correlation can be found in the age and strength of a human being.

As one gets increased in age e.g 70and above, activities that were done, example like running or any other fitness may not be carried out anymore by such individual like when he or she was in teens age.

Zero correlation
Zero correlation indicates that there is no relationship at all between variables in consideration.

A perfect example of this correlation is the number of people driving on a street in Port Harcourt and Abuja. There is no relationship at all. The two can't be linked together.

![Screenshot_20220329-063916_2.png](https://images.hive.blog/DQmXYieG566oSV1MPX7fUt3UUKnkxjeqcENjP3jewQBvBzr/Screenshot_20220329-063916_2.png)<center> Taken with smartphone Techno PoP5 </center>

Example of questions that can be answered by spearman correlation

The following examples of questions can be figured out using speaean correlation analysis.

Does people who are highly paid obtain satisfaction with life.

Does the reading efficiency relates with the outcome of result?

How to carryout spearman correlation in SPSS 

To carryout spearman correlation analysis,

Go-to Analyze menu

Click on correlate
Select bivariate

You can choose to add the two variables you wish to find the relationship.

Be sure of clicking kendalis tab and spearman rho.

Kendalis tab will show how many concordance pair exist between the variables.

Output of spearman correlation analysis
The output of spearman correlation analysis

The output of the spearman correlation consist of one table as seen below.
![IMG_20220329_62846.jpg](https://images.hive.blog/DQmbNHPoX9QK8h55hkN3kz7nKQ7ntH7aeiPPFnheYVq2yeD/IMG_20220329_62846.jpg)<center> Taken with smartphone Techno PoP5 </center>

This was a test by statistics solution to findout if reading and writing test are correlated.

Kandauli tab will calculate how many same pairs exist in the sample, this will give us a high belief concerning  the result of spearman correlation.

The second table is the spearman rho which indicates that there is a relationship between reading test grade and writing test grade.

If you score a high grade in reading, there is a tendency that you will also score a high grade in writing.

The null hypothesis for bivariate correlation applies for spearman correlation.

Conclusively
Spearman correlation is concerned with ranks linkage. It is also the type of correlation used for ordinal data analysis.

References
S.C Gupta (2012), Fundamentals of statistics.

Statistics solutions, Statistical Analysis,  "Spearman correlation test"