The manufacturing sector diversifies along the industry average. The two methods also agree on the analysis for hypothesis 2. The communication services firms achieve lower than average growth, while the manufacturing and business service firms achieve higher than average growth. This study demonstrates that visualization techniques can complement statistical analysis. They can provide a direction for more precise measurement of certain aspects of data relationships.
Visualization also sheds more light on the relationships.
For example, the visualizations show that a linear model is a poor choice for the data. The combination of visualization and traditional statistical techniques provide more information about the problem under study than either method alone. Areas for Further Developments Visualization methods provide an avenue of rapid and information intensive analysis of raw and resultant data. They can be used to examine the effects of outliers, interactions between data and the structural content of data. The technique of three-dimensional scatter plots, commonly used in statistical data analysis, provides a base on which further tools can be developed for use in a managerial setting.