Data-set for Cases of Sexually Transmitted Diseases: Jos University Teaching Hospital, Plateau State,Nigeria

This procedure is designed to summarize several columns of quantitative data. It will calculate various statistics, including
correlations, covariances, and partial correlations. Also included in the procedure are a number of multivariate graphs, which
give interesting views into the data. Use the Tabular Options and Graphical Options buttons on the analysis toolbar to access
these different procedures.

After this procedure, you may wish to select another procedure to build a statistical model for your data. Depending on your
goal, one of several procedures may be appropriate. Following is a list of goals with an indication of which procedure would be
appropriate:
GOAL: build a model for predicting one variable given values of one of more other variables.
PROCEDURE: Relate - Multiple Factors - Multiple Regression
GOAL: group rows of data with similar characteristics.
PROCEDURE: Describe - Multivariate Methods - Cluster Analysis
GOAL: develop a method for predicting which of several groups new rows belong to.
PROCEDURE: Relate - Classification Methods - Discriminant Analysis
GOAL: reduce the number of columns to a small set of meaningful measures.
PROCEDURE: Describe - Multivariate Methods - Factor Analysis
GOAL: determine which combinations of the columns determine most of the variability in your data.
PROCEDURE: Describe - Multivariate Methods - Principal Components
GOAL: find combinations of the columns which are strongly related to each other.
PROCEDURE: Describe - Multivariate Methods - Canonical Correlations