《统计运算与处理-马力.doc》由会员分享，可在线阅读，更多相关《统计运算与处理-马力.doc（6页珍藏版）》请在金锄头文库上搜索。
1、课程大纲课程编号： 02814900 授课对象： I-PhD 2010 课程名称：统计运算与处理 英文名称： Data Computing and Analysis周学时 /总学时： 3/30 学 分：2任课教师： Dr. Li Ma 开课学期： Fall 2010先修课程： Probability, Linear algebra Time: Wednesday 13:00-16:00, Sept. 8-Nov. 24 Location: Computer lab at Guanghua Building任课教师联系方式： (preferred) 6275-3185, Room 353 (G
2、uanghua No. 2 Building)辅导、答疑时间： Every Tuesday 9:00 11:00 am, and by appointment助教：解蕴慧， 一、课程概述 This course provides a doctoral-level overview of processing data for research, especially in the field of management. The course will include lectures, exercises, exams, lab-practices, etc. This course is
3、not simply a “statistics” one, but emphasizes the application of statistical techniques in management research. You will learn more detailed nuances of relevant statistical procedures in different courses; this course is designed to give you a good start of making sense of others research and of con
4、ducting your own research. In addition, this course is not a “software” one: although I will use Excel, SPSS, AMOS, HLM, and other software to illustrate how you can “get things done,” the focus will be how to make sense of the statistic outcomes obtained from the software and how to conduct next st
5、eps in your research. 二、课程目标 After successfully completion of this course, students shall be able to run fundamental data analyses in research and test hypotheses with analysis results. Students shall be familiar with the whole data processing techniques (including data collection processes), and mo
6、re detailed, advanced techniques can be learned through later courses or by self-learning activities. Because this course is intended to help research-oriented students to grasp the essence of research question-data interactions, students are encouraged to explore discipline-related datasets and use
7、 methods learned in class to analyze them. You can find many datasets provided by me, in disciplines related to marketing, strategic management, organizational behavior, and human resource management. In addition, you can also find other datasets in conducting your own analyses. One approach is to t
8、alk to your mentor (I assume you have one) and analyze some used or unused datasets. Possibly after analyzing the data effectively you may find some interesting results that are publishable. Statistics for I-PhD at Guanghua, Fall 2010 三、内容提要及学时分配 Week Date Topic Note The Logic of Research and Data;
9、Anderson et al. Ch1; 1 09/08 Level of measurement; Types of variables Huff (1954) Data Handling Processes Anderson et al. Ch22 09/15 09/22 Break: Mid-autumn Festival Describing data using graphs and numbers 3 3 4 09/29 Matrix algebra Sharma Ch3 5 6 10/13 Measurement and scale creation, reliability a
10、nd validity; (Principal component analysis; EFA and CFA) Pedhazur & Schmelkin (1991) Ch 4-5 Lattin et al. Ch4-6 10/06 Break: Nationals Day Holiday 7 10/20 Comparing two groups Anderson 10.2, 10.3; 12.1, 12.2 8910 10/27 11/03 11/10 Midterm Comparing multiple groups: ANOVA and MANOVA The logic of hypo
11、thesis testing (Type I and Type II errors); Correlation and multiple regression Anderson Ch13 Iversen & Norpoth (1987) Anderson Ch14, 15; Pedhazur & Schmelkin (1991) Ch17, 18 11 11/17 Multivariate Analyses; Calculating mediation and moderation Sharma (1996) Ch711; Lattin et al. (2003) Ch 7-10, 12 12
12、/01 Reading week: No class 12 11/24 Reporting analyses results Bem (2002) 13 14 12/08 Final exam四、教学方式 Lectures will be given in our in-class sessions. Most sessions will include software demonstration to aid your first-hand experiences. We will also have in-class exercises and a few homework assign
13、ments. Midterm and final exams are to consolidate your understanding of working with data. 五、教学过程中 IT工具等技术手段的应用 Presentations may be facilitated with PPT. SPSS and some additional software will be used. The statistical software SPSS will be used for illustration and students shall be familiar in usi
14、ng it (but using any other software is encouraged). Statistics for I-PhD at Guanghua, Fall 2010 六、教材 Optional Anderson, D. R., Sweeney, D. J., & Willams, T. A. 2005. Statistics for Business and Economics (9th ed.). Cincinnati, CT: SouthWestern College. Published in China by China Machine Press. 七、参考
15、书目 Sharma, S. (1996). Applied multivariate techniques. New York: John Wiley & Sons, Inc. Iversen, G. R. & Norpoth, H. 1987. Analysis of variance (2nd ed.). Newbury Park, CA: Sage. Lattin, J. M., Carroll, J. D., & Green, P. E. 2003. Analyzing multivariate data. Pacific Grove, CA: Brooks/Cole-Thompson Learning. Published in China by China Machine P
