Page 262 - DMGT209_QUANTITATIVE_TECHNIQUES_II

Unit 14: Multivariate Analysis

target is fixed and based on the past sales achieved by them about which, the data is available in Notes
the company. It is also announced that marketing executives who add 15 or more distributors
will be given a Maruti omni-van as prize. Those who generate between 5 and 10 distributors
will be given a two-wheeler as the prize. Those who generate less than 5 distributors will get
nothing. Now assume that 5 marketing executives won a Maruti van and 4 won a two-wheeler.
The company now wants to find out, “Which activities of the marketing executive made the
difference in terms of winning a prize and not winning the prize”. One can proceed in a number
of ways. The company could compare those who won the Maruti van against the others.
Alternatively, the company might compare those who won, one of the two prizes against those
who won nothing. It might compare each group against each of the other two.
Discriminant analysis will highlight the difference in activities performed by each group members
to get the prize. The activity might include:
1. More number of calls made to the distributors.
2. More personal visits to the distributors with advance appointments.
3. Use of better convincing skills.

Discriminant Analysis

1. What variable discriminates various groups as above; the number of groups could be two
or more. Dealing with more than two groups is called Multiple Discriminant Analysis
(M.D.A).
2. Can discriminating variables be chosen to forecast the group to which the brand/person/
place belong to?
3. Is it possible to estimate the size of different groups?

Self Assessment

Fill in the blanks:
1. ....................... analysis is used if there are more than 2 variables.
2. An advantage of the non-metric models is that they permit the researcher to .......................
and ....................... preference data.
3. ....................... analysis is used by those who buy our brand and those who buy competitors’
brand.

14. 2 Factor Analysis

The main purpose of Factor Analysis is to group large set of variable factors into fewer factors.
Each factor will account for one or more component. Each factor a combination of many variables.
There are two most commonly employed factor analysis procedures. They are:
(1) Principle component analysis
(2) Common factor analysis.
When the objective is to summarise information from a large set of variables into fewer factors,
principle component factor analysis is used. On the other hand, if the researcher wants to analyse
the components of the main factor, common factor analysis is used.

Example: Common factor – Inconvenience inside a car. The components may be:
1. Leg room.
2. Seat arrangement.

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