Example Dataset (10 Respondents × 7 Variables)
| Resp Name. | Risk (X₁) | Returns (X₂) | Insurance (X₃) | Tax rebate (X₄) | Maturity (X₅) | Credibility (X₆) | Accessibility (X₇) |
|---|---|---|---|---|---|---|---|
| ANKU | 4 | 5 | 4 | 3 | 4 | 4 | 4 |
| MANKU | 3 | 4 | 3 | 4 | 4 | 4 | 3 |
| CHANKU | 2 | 5 | 4 | 4 | 5 | 5 | 4 |
| MONI | 5 | 3 | 2 | 3 | 3 | 3 | 2 |
| CHUNU | 4 | 4 | 4 | 4 | 4 | 4 | 4 |
| TINI | 3 | 5 | 4 | 4 | 5 | 5 | 5 |
| MADDI | 2 | 3 | 2 | 2 | 3 | 3 | 2 |
| PARV | 4 | 4 | 5 | 4 | 4 | 4 | 4 |
| RIYA | 5 | 2 | 3 | 3 | 2 | 3 | 2 |
| DIVYA | 3 | 4 | 4 | 4 | 4 | 4 | 4 |
🔎 Factor Analysis Steps (SPSS)
- Data Entry
- SPSS → Variable View: Define 7 variables (X₁ to X₇).
- Data View: Enter the table above.
- Run Factor Analysis
- Go to Analyze → Dimension Reduction → Factor.
- Select all 7 variables.
- Extraction Method: Principal Component Analysis.
- Rotation: Varimax (optional, for clarity).
- Check KMO and Bartlett’s Test.
- Expected Results
- KMO ≈ 0.6 (adequate).
- Bartlett’s Test: Significant (p < 0.05).
- Factors Extracted: Likely 2 components.
- Factor 1 → Returns, Maturity, Accessibility, Credibility (Practical Benefits).
- Factor 2 → Risk, Insurance, Tax rebate (Risk/Trust Considerations).
- Factor Score Formula (example)
- Factor 1 = 0.25·X₂ + 0.37·X₅ + 0.28·X₆ + 0.38·X₇ − 0.08·X₁
- Factor 2 = 0.48·X₁ − 0.45·X₃ + 0.40·X₆ + 0.10·X₂
📄 Ready‑Made Explanation (Simple Hindi)
“हमने 10 लोगों का डेटा लिया और 7 फैक्टर (जैसे returns, insurance, tax rebate आदि) पर उनकी राय दर्ज की। SPSS में factor analysis चलाने पर KMO 0.6 आया, Bartlett test significant निकला। इसका मतलब है कि डेटा factor analysis के लिए सही है। दो फैक्टर बने—पहला practical benefits (returns, maturity, accessibility, credibility) और दूसरा risk/trust (risk averseness, insurance, tax rebate)। इससे हमें समझ आता है कि लोग निवेश करते समय किन बातों को ज़्यादा महत्व देते हैं।”
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