﻿ Spearman's Rank Correlation

# Spearman's Rank Correlation

### Statistics > Regression > Spearman Rank

Performs Spearman Rank Correlation.

The Spearman's rank is a nonparametric version of the Pearson correlation coefficient, based on the ranks of the data rather than the actual values. It is appropriate for ordinal data, or for interval data that do not satisfy the normality assumption. Values of the coefficient range from -1 to +1. The sign of the coefficient indicates the direction of the relationship, and its absolute value indicates the strength, with larger absolute values indicating stronger relationships.

### Dialog box items

Samples in different columns:
Choose if the data of the two samples are in separate columns.

oFirst Sample: Enter the column containing one sample.

oSecond Sample: Enter the column containing the other sample

Samples in one column:
Choose if the sample data are in a single column, differentiated by factor levels in a second column.

oSamples: Enter the columns containing the sample data.

oFactor and Levels: Enter the columns containing the sample factor, and select the levels.

Report:
The display of outputs of VisualStat.

### Data

Use symmetric quantitative variables for Pearson’s correlation coefficient and quantitative variables or variables with ordered categories for Spearman’s rho and Kendall’s tau-b.

### Options

Alternative Hypothesis:
Enter Two-sided, Upper One-sided, or Lower One-sided. If you choose an One-sided hypothesis test, an upper or lower confidence bound will be constructed, respectively, rather than a confidence interval.

Confidence Level:
Enter the level of confidence desired. Enter any number between 0 and 100. Entering 90 will result in a 90% confidence interval. The default is 95%.

### Example

We explore the relation between the efficiency of the employees and their sociability. Efficiency and sociability are appreciated by a test. The results of this test for each of the 12 employees are given in a dataset.

1.Open the DataBook reg.vstz

2.Select the sheet emp

3.Choose the tab Statistics, the group Regression and the command Spearman Rank

4.Select group Samples in different columns

5.In First Sample, select Eff. In Second Sample, select Soc.

6.Click OK

Report window output

Spearman's Rank Correlation

Test of independence between two variables

null hypothesis: true The rank correlation in the population is zero

Eff x Soc

N               12

Type of Test    Two-sided

Spearman's Rho  0.8182

Distribution    Student Approximation

t-value         4.5000

p-value         0.0011

alpha-level     0.05

Conclusion      Reject the Null Hypothesis

 See Also: