XLSTAT - Correlations and Similarity/Dissimilarity Matrix
Similarity and dissimilarity tool in XLSTAT
XLSTAT helps you to explain the relationships between variables in term of similarities and dissimilarities by measuring their proximity.
This tool offers a large number of proximity measurements between a series of objects whether they are in rows (usually the observations) or in columns (usually the variables).
Similarities and dissimilarities
The proximity between two objects is measured by measuring at what point they are similar (similarity) or dissimilar (dissimilarity).
The indexes offered depend on the nature of the data:
Similarities and dissimilarities for quantitative data
The similarity coefficients proposed by the calculations from the quantitative data are as follows: Cosine, Covariance (n-1), Covariance (n), Inertia, Gower coefficient, Kendall correlation coefficient, Pearson correlation coefficient, Spearman correlation coefficient.
The dissimilarity coefficients proposed by the calculations from the quantitative data are as follows:
- Bhattacharya's distance,
- Bray and Curtis' distance,
- Canberra's distance,
- Chebychev's distance,
- Chi² distance,
- Chi² metric,
- Chord distance,
- Squared chord distance,
- Euclidian distance,
- Geodesic distance,
- Kendall's dissimilarity,
- Mahalanobis distance,
- Manhattan distance,
- Ochiai's index,
- Pearson's dissimilarity,
- Spearman's dissimilarity.
Similarities and dissimilarities for binary data
The similarity and dissimilarity (per simple transformation) coefficients proposed by the calculations from the binary data are as follows:
- Dice coefficient (also known as the Sorensen coefficient),
- Jaccard coefficient,
- Kulczinski coefficient,
- Pearson Phi,
- Ochiai coefficient,
- Rogers & Tanimoto coefficient,
- Sokal & Michener's coefficient (simple matching coefficient),
- Sokal & Sneath's coefficient (1),
- Sokal & Sneath's coefficient (2).
Similarities and dissimilarities for qualitative data
The similarity coefficients proposed by the calculations from the qualitative data are as follows: Cooccurrence, Percent agreement.
The dissimilarity indexes proposed by the calculations from the qualitative data are as follows: Percent disagreement.
This analysis is available in the XLStat-Basic addin for Microsoft Excel™