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Multivariate statistical analysis

Multivariate statistical analysis. Introductions and basic data analysis. Multivariate . Variate ( 變量 ) vs. variable ( 變數 ) The attributes that the researcher concerned and observed performance The attributes that the researcher could operate for the expected performance

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Multivariate statistical analysis

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  1. Multivariate statistical analysis Introductions and basic data analysis

  2. Multivariate • Variate (變量) vs. variable (變數) • The attributes that the researcher concerned and observed performance • The attributes that the researcher could operate for the expected performance • Uni-variate (單變量) vs. multi-variate (多變量) • Single concerned performance • Multiple concerned performance vector

  3. Measurement scale • Nominal • Ordinal • Interval • Ratio • ref. p.10 表1.2-1 四種衡量尺度之比較

  4. Four types of measuring scale

  5. Measuring Variables • Measuring variables: used to describe the attitudes of specific concerned attributes • Analytical variables: internal scale, ratio scale • Categorical variables: nominal scale, ordinal scale • ref. p.11, 表1.2-2,-3,-4

  6. Example

  7. Cost of measurement • Error cost: the impact resulted from the deviation to the true attitude • Measuring cost: the difficulty of accurate measuring

  8. Reliability • Retest reliability • Verify the stability of the responses • Split half reliability • Designing the contrast questions • Cronbach’s α (>0.7)

  9. Cronbach’s α

  10. Validity • Effectiveness to reflect the concerned issues • Content validity • Criteria-related validity • Construct validity

  11. Problems of validity

  12. Likert scale • Quasi-interval scale • 5-scale, 7-scale, (in the form of 2/3 negative scale and 2/3 positive scale around the original)

  13. Data format • Cases: the observant, the experimental subjects/objects • Variables: the set of concerned attributes • Observations: the collected data • Observation vector: the set of all attributes retained from a specific case

  14. Data format

  15. Classification of multivariate models • Functional relation model • Responsive variates=f (independent variables) • Interdependence relation model • Variables interdependence • Cases interdependence • Systemic relation model • Path analysis • LISREL model • ref. p.33, 表1.7-1 多變量統計模式之歸類; p.40,表1.7-2; p.41,表1.7-3

  16. Multivariate analysis models

  17. Multivariate analysis models

  18. Multivariate analysis models

  19. SAS/SPSS introductions

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