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.
•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.
The display of outputs of VisualStat.
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.
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.
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%.
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.
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
Type of Test Two-sided
Spearman's Rho 0.8182
Distribution Student Approximation
Conclusion Reject the Null Hypothesis