Page 263 - DMGT209_QUANTITATIVE_TECHNIQUES_II

Quantitative Techniques-II

Notes 3. Entering the rare seat.
4. Inadequate dickey space.
5. Door locking mechanism.

Principle Component Factor Analysis
Purposes: Customer feedback about a two-wheeler manufactured by a company.
Method: The M.R manager prepares a questionnaire to study the customer feedback. The
researcher has identified six variables or factors for this purpose. They are as follows:
1. Fuel efficiency (A)
2. Durability (Life) (B)
3. Comfort (C)
4. Spare parts availability (D)
5. Breakdown frequency (E)
6. Price (F)
The questionnaire may be administered to 5,000 respondents. The opinion of the customer is
gathered. Let us allot points 1 to 10 for the variables factors A to F. 1 is the lowest and 10 is the
highest. Let us assume that application of factor analysis has led to grouping the variables as
follows:
A, B, D, E into factor – 1
F into Factor -2
C into Factor - 3
Factor - 1 can be termed as Technical factor;
Factor - 2 can be termed as Price factor;
Factor - 3 can be termed as Personal factor.
For future analysis, while conducting a study to obtain customers’ opinion, three factors
mentioned above would be sufficient. One basic purpose of using factor analysis is to reduce the
number of independent variables in the study. By having too many independent variables, the
M.R study will suffer from following disadvantages:
1. Time for data collection is very high due to several independent variables.
2. Expenditure increases due to the time factor.
3. Computation time is more, resulting in delay.
4. There may be redundant independent variables.

Did u know? What is correspondence analysis?
Correspondence analysis is a descriptive/exploratory technique designed to analyze
simple two-way and multi-way tables containing some measure of correspondence between
the rows and columns. The results provide information which is similar in nature to those
produced by Factor Analysis techniques, and they allow one to explore the structure of
categorical variables included in the table. The most common kind of table of this type is
the two-way frequency cross-tabulation table.

In a typical correspondence analysis, a cross-tabulation table of frequencies is first standardized,
so that the relative frequencies across all cells sum to 1.0. One way to state the goal of a typical
analysis is to represent the entries in the table of relative frequencies in terms of the distances
between individual rows and/or columns in a low-dimensional space.

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