Attribute Mapping - TEAM A - Operations

In the last session we learnt about how to use proximity data in Permap using SimilarityList and DissimilarityList. Today we will learn how attribute data can be used in Permap.

What is an attribute? An attribute is some aspect of an object. It may be called a factor, characteristic, trait, property, component, quantity, variable, dimension, parameter etc.

In attribute mapping, each object is represented by a set of attribute values and the proximities between objects are calculated from the attribute data using any of several standard relationships.

The format that needs to be used is:

NOBJECTS=6              Gives the number of objects in the analysis.

NATTRIBUTES=3         Gives the number of attribute values for each object.

ATTRIBUTELIST          Announces that attribute values follow.

Attributes Evaluation Screen

This screen is divided into four parts:  Analysis options, Attribute selection, Attribute fit plot and Notes.

Analysis Option:

It provides five ways to superimpose attribute gradient vectors on the MDS map. Each option has on-line context-sensitive information provided in a "Notes" text box at the bottom of the Attributes menu screen. If no attributes are given in the problem definition, then the Attributes menu entry is disabled.

Attribute Selection:

It is a box that lists all available attributes. By highlighting a member of this box you determine which attribute is to be used for the Attribute Fit plot and for plotting the various on-map gradient vectors. If you have more than seven attributes you will need to use the right arrow to highlight the “missing” attribute numbers in the Attribute Selection List box.

Attribute Fit Plot:

The Attribute Fit plot is a scatter plot that shows how well one or all of the attributes are described by an optimally oriented uni-variant gradient running across the map. As usual, the coefficient of determination, R2, is the key measure. A perfect fit results in R2 = 1, whereas random behavior causes R2 to approach zero.

The above figure shows that the attributes 1and 2 are influencing each other. Similarly attribute 4 and 6 influence each other. Attribute 3 and 5 are opposite in direction. That means they are inversely related i.e. if attribute 3 improves then attribute 5 reduces.

Here one needs study which attribute needs to be improved for which store and what needs to be done for the same.

Team A

Ankur Mundra

14009