Sunday, 28 August 2011

About SPSS and its applications.

SPSS is a computer program used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, statistical analysis, and collaboration & deployment (batch & automated scoring services).

Organizations count on IBM SPSS Modeler to improve outcomes and reach their goals. Options other than SPSS are SAS, Statistica, Minitab.

Few applications of SPSS in different sectors-

Marketing firms.

Banking, Insurance companies and financial services firms make their marketing campaigns more effective, evaluate credit risk more reliably and spot potentially fraudulent activities more efficiently.

Telecommunications companies develop more intimate customer relationships in order to build loyalty and reduce customer defection or "churn".

Retailers improve their assortment planning and fine-tune their marketing and customer loyalty efforts.

Utilities and energy suppliers offer more personalized service to customers. Analytics also plays a role in preventive maintenance, which results in greater reliability at less cost.

Government agencies manage functions as diverse as tax audit selections, military force recruitment and proactive policing and public safety.

Healthcare organizations use predictive intelligence to proactively manage their resources and fine-tune their practices to provide better patient care.

SPSS is a very useful tool in all the fields where data processing is required.

As in the previous blogs cluster analysis is explained nicely so I would like to add few points about various ways of measuring distances. Though we use Euclidean distance for the calculations.

Distance measure

An important step in most clustering is to select a distance measure, which will determine how the similarity of two elements is calculated. This will influence the shape of the clusters, as some elements may be close to one another according to one distance and farther away according to another.

Common distance functions-

The Euclidean distance (also called distance as the crow flies or 2-norm distance). A review of cluster analysis in health psychology research found that the most common distance measure in published studies in that research area is the Euclidean distance or the squared Euclidean distance.

The Manhattan distance- is the new metric in which the distance between two points is the sum of the absolute differences of their coordinatesThe Mahalanobis distance corrects data for different scales and correlations in the variables.

The angle between two vectors can be used as a distance measure when clustering high dimensional data.

The Hamming distance measures the minimum number of substitutions required to change one member into another.





Author- Aakash bavariya (13001)

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