The basics of survey processing > Data Analysis
Multivariate analysis
- Correlations- Correlation matrices
- Simple or multiple regressions
- AFC - Factorial correspondence analysis
- PCA - Principal component analysis
- MFA - Multiple factorial analysis
- Typology (Cluster analysis)
- Segmentation
- Hierarchical classification
- Discriminant analysis
Conducting analyses in DAISIE
All the analyses mentioned above are available in DAISIE. The functioning of these analyses has been studied to enable the user to concentrate on the methodology and results, and not lose any time preparing the variables they need. For example, DAISIE knows the kind of variable needed in an analysis and also knows how to transform and optimise the variables. Another example is the no answers in variables, the presence of which is always to be avoided in analyses; they are also dealt with automatically in DAISIE based on the choice made by the user.
Example of a hierarchical classification
Hierarchical classification conducted in DAISIE on the quantitative variable Q14N, which represents a battery of scores for 23 items:
Q14N – Your opinion about holidays
1- Holidays are about sunshine
2- Being on holiday is doing sporting activities from morning until evening
3- ...
23- It’s better to go to Tahiti once than to the seaside every year
The results produced by the hierarchical classification in DAISIE are: a table of distances, dendogram and table of clusters.
Dendogram of Q14N