Let's break down the process of performing factor analysis using the SPSS software. Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. Understanding the correct command sequence is crucial for running this analysis in SPSS.

In SPSS, statistical procedures are accessed through the 'Analyze' menu. Within the 'Analyze' menu, different techniques are grouped under various sub-menus. Factor analysis falls under the category of techniques used for dimension reduction or data reduction, as it aims to reduce a large set of variables into a smaller set of factors.

The standard path to access the Factor Analysis dialog box in SPSS typically involves the following steps:

1. Click on the 'Analyze' menu.
2. From the dropdown menu, select 'Dimension Reduction' (or 'Data Reduction' in some older versions like SPSS 17 or other contexts).
3. From the next sub-menu, select 'Factor...'.

Now, let's match this standard sequence with the options provided in the question:

• (a) Analyse: This corresponds to the first step, clicking the main 'Analyze' menu.
• (c) Data reduction: This corresponds to the sub-menu 'Dimension Reduction' or 'Data Reduction'.
• (b) Factor: This corresponds to the specific procedure 'Factor...' within the sub-menu.

Therefore, the correct sequence of commands to perform factor analysis in SPSS-17 is to first select the 'Analyse' menu, then navigate to the 'Data reduction' sub-menu, and finally select 'Factor'. This corresponds to the sequence (a), (c), and (b).

Here is a summary of the steps:

Revision Table: SPSS Factor Analysis Commands

Reviewing the commands for factor analysis in SPSS helps solidify the steps:

• Start with the main analysis menu.
• Locate the section for reducing dimensions or data.
• Select the specific factor analysis procedure.

Additional Information: Understanding Factor Analysis in SPSS

Factor analysis is a powerful tool in statistical analysis for exploring underlying structures in data. In SPSS, the Factor Analysis dialog box offers numerous options, including:

• Variable Selection: Choosing which variables to include in the analysis.
• Extraction Method: Selecting the method for extracting factors (e.g., Principal Components, Maximum Likelihood).
• Rotation Method: Choosing a method to rotate factors for better interpretability (e.g., Varimax, Promax).
• Scores: Options to save factor scores as new variables.
• Options: Setting criteria for extraction (e.g., Eigenvalue > 1), handling missing values, and displaying output like Kaiser-Meyer-Olkin (KMO) and Bartlett's Test of Sphericity.

Understanding these options after navigating the correct command sequence allows researchers to tailor the factor analysis to their specific research questions.