2 項進行中

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 進行中 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 進行中 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

加入行事曆

選擇訂閱 Google Calendar,或下載通用的 ICS 檔案。

使用 Google Calendar 時,Google 會收到這份課表的公開連結。

管理資料分析

Data Analysis for Management

學期
109-1
學分
0 學分
當期課號
5678
永久課號
IBM6093
開課單位
管理學院碩士在職專班-經管組
授課教師
丁承
類別
必修
上課時間表
週二
A
18:30–19:20
管理資料分析
TD
3 節連堂
B
19:30–20:20
C
20:30–21:20

* 根據陽明交大上課時間表所列

概述

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,並培養進一步研究的基礎。多變量部分置於最後兩週,為彈性補充教學內容。

先修科目

統計學

備註

無備註

教學方式

參考書籍: [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。

評分方式

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%。 4. 教學方法及教學相關配合事項(如網站、助教、圖書講義及資料庫等): 全程由教師講授,以板書為主,並提供SAS講義給同學參考使用。

課程大綱
  • 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. Introduction to Statistical Package SAS

    講授:
    3
  • 迴歸

    1. Multiple Regression 2. Multicollinearity, Variable Selection 3. The Dummy Variable Technique 4. Testing for Moderating Effects 5. Testing for Mediation Effects 6. Bootstrapping 7. Testing Homoscedasticity 8. Testing for Autocorrelation

    講授:
    21
  • 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 ANOVA 5. Nested Design

    講授:
    12
  • 類別資料分析

    1. Binary Logistic Regression 2. Cross-Validation

    講授:
    6
  • 構面縮減技術

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

    講授:
    6
週次計畫
週次主題
第 1 週

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

2020/09/15
第 2 週

Multiple Regression

2020/09/22
第 3 週

Multicollinearity and Variable Selection

2020/09/29
第 4 週

The Dummy Variable Technique

2020/10/ 6
第 5 週

Testing for Moderating and Mediation Effects

2020/10/13
第 6 週

Bootstrapping

2020/10/20
第 7 週

Testing Homoscedasticity

2020/10/27
第 8 週

Testing for Autocorrelation

2020/11/3
第 9 週

期中考

2020/11/10
第 10 週

One-Factor ANOVA

2020/11/17
第 11 週

Randomized Block Design (RBD) and Analysis of Covariance(ANCOVA)

2020/11/24
第 12 週

Two-Factor ANOVA (Balanced and Unbalanced)

2020/12/1
第 13 週

Nested Designs, Mixed Models

2020/12/8
第 14 週

Binary Logistic Regression

2020/12/15
第 15 週

Cross-Validation

2020/12/22
第 16 週

期末考

2020/12/29
第 17 週

Principal Components and Exploratory Factor Analysis

2021/1/5
第 18 週

Confirmatory Factor Analysis

2021/1/12
教科書

Kutner, M. H., Nachtsheim, C. J., Neter, J., and Li, W. (2005), Applied Linear Statistical Models (5th ed.), McGraw-Hill International Edition.

Office Hours
地點
教授研究室
時間
每週二16:00 ~ 18:00 (其他時間可先預約)
聯絡方式
cding@mail.nctu.edu.tw