課程資訊
課程名稱
 社會科學統計方法專題
STATISTICAL METHODS FOR THE SOCIAL SCIENCE 
開課學期
 97-1 
授課對象
 社會科學院  政治學研究所  
授課教師
 江瑞祥 
課號
 PS7002 
課程識別碼
 322 M3900 
班次
  
學分
 3 
全/半年
 半年 
必/選修
 必修 
上課時間
 星期二2,3,4(9:10~12:10) 
上課地點
 社法6 
備註
 國際關係，公共行政，本國政治，比較政治。
限碩士班以上
總人數上限：70人
外系人數限制：30人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/971322M3900 
課程簡介影片
 
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課程概述

This course is the first of a series of a year-long course in statistical methodologies designed for advanced undergraduate or graduate students. The aim of this course is to provide an overview of elementary descriptive and inferential statistics, with an emphasis on applications in social/political sciences. This course will introduce the student to common and useful statistical procedures with relevance to research conducted by social/political scientists. All social sciences students should be able to read and criticize statistics frequently presented in academic, media, and governmental reports. While understanding statistical theory is critical to this endeavor, this course attempts to balance theoretical and practical understanding of statistical concepts. 

課程目標
 Knowledge of mathematics through college algebra is required, but no more. For undergraduates, this course satisfies the math reasoning proficiency requirement. For graduate students, this course serves as a prerequisite for other social science statistics and methodology courses. In addition to the focus on social/economic/political/cultural research, this course differs from many other statistics courses in using computer applications as an integral part of training.  
課程要求
 Successful completion of the course depends on reading the texts and completing the assigned homework problems. On occasion, you will be asked to turn in your homework for grading and review. Your performance in the course will be evaluated on the basis of five homework assignments (total worth 50% of the final grade), an examination (worth 30% of the final grade), and a brief research paper (20%).

The research paper should demonstrate your competence in applying statistics to a specific research problem. You may choose among several research topics using actual social science data. You will develop a concise research hypothesis that can be tested with data and computer analysis. You should briefly identify the source of your research problem, formulate it as a hypothesis for testing with available data, execute the appropriate test, and draw conclusions about the validity of the hypothesis. The text of the paper should be about eight to ten typewritten, double-spaced pages in length (twelve pages is the maximum), in addition to tables and graphs as appropriate. Evaluation of this exercise will be based primarily on clarity of presentation and statistical craftsmanship rather than on the substantive or theoretical importance of the problem. You will select a topic and submit a one-page progress report outlining your hypotheses and data in late-November, and your final research paper is due on one week after the last day of class.
 
預期每週課後學習時數
  
Office Hours
 另約時間 備註： BY APPOINTMENT AT rchiang@ntu.edu.tw 
指定閱讀
  
參考書目
 - Agresti, Alan, and
Barbara Finlay, 2009,
Statistical Methods for the
Social Sciences, 4th
edition, Upper Saddle River,
NJ: Prentice Hall.

The textbook above has a 3rd
edition Chinese version sold
at local bookstores (社會統計
學，鄭宗琳、吳宇真譯，2002，
五南圖書出版). Many students
have found the text to be a
useful reference source for
subsequent classes and
research.

Many data analysis packages
are available and this
semester we will use SPSS®
which is easily available at
NTU and widely used in
teaching and industry.
However, if you wish, you
may use anything else but we
cannot promise support. Some
NTU Computing Labs support S-
PLUS®, SAS®, JMP®, EView®,
and STATA®. MATLAB® is also
a possibility for those who
want to do some programming.
 
評量方式
(僅供參考)
  
No.
項目
百分比
說明
1. 
 期中考 
0% 
  
2. 
 期末考 
30% 
  
3. 
 隨堂測驗 
0% 
  
4. 
 作業 
50% 
  
5. 
 報告 
20% 
  
 
課程進度
週次
日期
單元主題
第1週
 9/16  Introduction and Key Issues 
第2週
 9/23  Sampling and Measurement; Software Introduction 
第3週
 9/30  Descriptive statistics 
第4週
 10/07  Probability Distributions 
第5週
 10/14  Statistical Inference: estimation 
第6週
 10/21  Statistical Inference: Significance Tests 
第7週
 10/28  Comparison of Two Groups 
第8週
 11/04  ANOVA and Analyzing Association between Categorical Variables 
第9週
 11/11  Linear Regression and Correlation 
第10週
 11/18  Introduction to multivariate Relationships 
第11週
 11/25  Multiple Linear Regression 
第12週
 12/02  Multiple Linear Regression 
第13週
 12/09  Multiple Regression Recap 
第14週
 12/16  Regression Assumptions 
第15週
 12/23  Logistic Regression 
第16週
 12/30  Nonparametric Statistical Methods 
第17週
 1/06  Special Topics; Take Home Final