統計方法與資料分析

本課程介紹單變量統計線性模式(包括迴歸(regression)、變異數分析(ANOVA)、和共變數分析(ANCOVA)),類別資料分析之二元羅吉斯迴歸 (binary logistic regression) 以及多變量之構面縮減技術(包括主成份分析(principal components)、探索性因素分析(exploratory factor analysis, EFA)及驗證性因素分析(confirmatory factor analysis, CFA)),目的是使同學對這些方法的觀念有正確的認識與了解,另亦熟悉統計套裝軟體SAS的對應操作方法,期有助於同學在管理上的應用,並培養研究的基礎。

統計學

無備註

全程由教師講授,以板書為主,並提供講義給同學參考使用。 因應疫情採線上教學時,使用 Google Meet,會議連結為https://meet.google.com/ayi-trkz-nsn。

1. 學期作業: 期中考後有一次學期作業,教科書各章後之習題請自行練習,解答在書末光碟中。 2. 考試狀況: 期中考與期末考各一次。 3. 評量方法: 作業 20%,期中考 30%,期末考 50%。

• 統計在管理研究上扮演的角色

  1. The Role of Statistical Methods and Data Analysis in Management 2. A General Introduction to Statistical Package SAS

  講授：

  3

• 迴歸

  1. Multiple Regression, Collinearity 2. General Linear Test 3. The Dummy Variable Technique 4. Testing for Moderating Effects 5. Testing for Mediation Effects and Bootstrapping 6. Testing Homoscedasticity 7. Testing for Autocorrelation

  講授：

  15

• 變異數分析/共變數分析

  1. One-Factor ANOVA 2. Randomized Block Design 3. Analysis of Covariance 4. Two-Factor Crossed/Nested Designs

  講授：

  12

• 類別資料分析

  1. Binary Logistic Regression 2. Cross-Validation

  講授：

  3

• 構面縮減技術

  1. Principal Components 2. Exploratory Factor Analysis 3. Confirmatory Factor Analysis

  講授：

  9

Kutner, M. H., Nachtsheim, C. J., Neter, J., and Li, W. (2005), Applied Linear Statistical Models (5th ed.), McGraw-Hill International Edition. 參考書籍與文獻: [1] Afifi, A. A. and Clark, V. (1990), Computer-Aided Multivariate Analysis (2nd ed.), New York: Van Nostrand Reinhold. [2] Agresti, A. (2007), An Introduction to Categorical Data Analysis (2nd ed.), New York: Wiley. [3] Allison, P. D. (1991), Logistic Regression Using the SAS System: Theory and Application, Cary, NC: SAS Institute Inc. [4] Baron, R. M., and Kenny, D. A. (1986), The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, Journal of Personality and Social Psychology, 51, 1173–1182. [5] Berenson, M. L., Levine, D. M. and Goldstein, M. (1983), Intermediate Statistical Methods and Applications: A Computer Package Approach, Englewood Cliffs, NJ: Prentice-Hall. [6] Draper, N. R. and Smith, H. (1998), Applied Regression Analysis (3rd ed.), New York: Wiley. [7] Freund, R. J. and Littell, R. C. (2000), SAS System for Regression (3rd ed.), Cary, NC: SAS Institute Inc. [8] Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.), Upper Saddle River, NJ: Pearson Education. [9] Hosmer, D. W. and Lemeshow, S. (1989), Applied Logistic Regression, New York: Wiley. [10] Johnson, R. A. and Wichern, D. W. (2007), Applied Multivariate Statistical Analysis (6th ed.), Pearson International Edition. [11] Kleinbaum, D. G., Kupper, L. L., Muller, K. E. and Nizam, A. (1998), Applied Regression Analysis and Other Muitivariable Methods (3rd ed.), Boston: Duxbury Press. [12] Littell, R. C., Milliken, G. E., Stroup, W. W., Wolfinger, R. D., and Schabenberger, O. (2006), SAS for Mixed Models (2nd ed.), Cary, NC: SAS Institute Inc. [13] Littell, R. C., Stroup, W. W., and Freund, R. J. (2002), SAS for Linear Models (4th ed.), Cary, NC: SAS Institute Inc. [14] Morrison, D. F. (1990), Multivariate Statistical Methods (3rd ed.), New York: McGraw-Hill. [15] O’Rourke, N., Hatcher, L. and Stepanski, E. J. (2005), A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics (2nd ed.), Cary, NC: SAS Institute Inc. [16] Preacher, K. J., and Hayes, A. F. (2004), SPSS and SAS procedures for estimating indirect effects in simple mediation models, Behavior Research Methods, Instruments, and Computers, 36, 717–731. [17] Rencher, A. C. (1995), Methods of Multivariate Analysis, New York: Wiley. [18] Strokes, M. E., Davis, C. S., and Koch, G. G. (1995), Categorical Data Analysis Using the SAS System, Cary, NC: SAS Institute Inc. [19] 鍾惠民、吳壽山、周賓凰、范懷文 (民95),「財金計量」(修正版),台北市:雙葉書廊。

地點

教授研究室

時間

每週一 14:00 ~ 16:00

聯絡方式

cding@mail.nycu.edu.tw