NOTICE: The following example has been realized by using an old version of T-LAB (3.0). The latest version (T-LAB 7.0) includes new tools and a new charting system. Click here to find out more. T-LAB functions used in this short example are those highlighted in red in the image on the right. For futher information about T-LAB functions click here. To consult more samples click here. To download the demo click here.

Sixty civil service executives, by means of a short questionnaire, have been asked to identify and to describe in a few words their work obstacles, the measures to make and the needed resources.

Their responses have been quickly codified (one variable: THEMe; three categories: OBSTACle, MEASURe, RESOURce) and gathered in a single corpus.

In the first instance, in order to explore the local meaning of some key-words, we have used the Associations option.
In the graphs, the selected words are placed in the center; the others are distributed around it, each at distance proportional to its degree of association (cosine coefficient): the shorter the distance, the greater the degree of association. The significant relationships are therefore one-to-one, to the central word and to each of the others.

In the second place by means of the Specificities option we have distinguished the typical words, i.e. the over used in each answer subset.

OBSTACLES	MEASURES	RESOURCES

Eventually, in order to explore the similarity/dissimilarity relationships between the corpus subsets, we have used a Correspondence Analysis. The following chart shows the three objects in a bi-dimensional space.

The following table, by means of a test value, describes the significant characteristics of the horizontal axis .