Spss

FACTOR ANALYSIS

OBJECTIVE

Alpha Car manufacturer wish to release a small car into the market. The main objective of the below analysis is to determine the factors/variables that potential customers take into consideration while purchasing a car.

METHOD

The factor analysis has been done using IBM SPSS Statistics Data Editor.

ANALYSIS

The 10 variables are expressed as follows:

1) The price of the car should be reasonable (V1).

2) Fuel mileage of the car should be at least 17 km/hr (V2).

3) A small car should be easy to maintain and to be serviced (V3).

4) Seating should be comfortable for four adults (V4).

5) A small car should have adequate leg space and headroom (V5).

6) Brakes are the most critical part of a small car (V6).

7) Collapsible steering column should be standard equipment in all the new cars (V7).

8) Power steering is a must (V8).

9) Interior accessories of a small car should be attractive (V9).

10) Adequate space for luggage (V10).

Data have been collected from 20 potential customers about their perceptions and image attributes of small cars, SPSS was used to run a factor analysis on the responses as shared by them.

Following are the excerpts from the report as generated by the Software

KMO and Bartlett's Test |

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | .627 |

Bartlett's Test of Sphericity | Approx. Chi-Square | 166.498 |

| Df | 45 |

| Sig. | .000 |

The Kaiser-Meyer-Olkin Measure is 0.627 (which is more than 0.5). Hence, the data fits the model. The significance level of Bartlett’s Test of Sphericity tells whether overall correlation matrix has some significant correlation or not. The significance level is 0.000 (which is less than .005). Thus, we can safely conclude that factor analysis, which is based on correlations between variables, is appropriate.

Total Variance Explained |

Component | Initial Eigenvalues | Extraction Sums of Squared Loadings | Rotation Sums of...