Qualitative Data Analysis Method

Course No.: SMJ2221132       Credit(s):2

Course Description

This course mainly introduces qualitative data analysis method which widely used in many fields such as social science, behavioral science, biomedicine, public health, marketing, education and agricultural science. It includes the basic contents of the exploratory data analysis and inferential statistical analysis of classified data and sequencing data. It requires students to master qualitative data description statistics and inferred statistical knowledge systematically, including parameter estimation, hypothesis testing, regression analysis model and variance analysis model and so on.

Course Learning Outcomes

The student learning outcomes are what student would be able to know and to do on the completion of this course. In details are:

lUnderstand the relationship and difference between qualitative data analysis and other statistical analyses

lMaster contingency table exploratory analysis in qualitative data analysis, contingency table chi square test, construction, estimation and testing generalized linear models of classification and sequencing data logistic regression.

Relationship to Other Courses

The prerequisites for this course are Statistics and Probability Theory and Mathematical Statistics.

Textbook and Reading Lists

Textbook:

Agrest, Introduction to Attribute Data Analysis. Trans, Shumei Zhang,etc, Higher Education Press, 2008.12

Suggested reading lists:

Jinlong Wang, Xiaojun Liang, Qualitative Data Statistical Analysis (1st edition). China Statistics Press, 2008.7.

Ping Zhao, Qualitative Data Statistical Analysis (1st edition). Social Sciences Literature Press,2014.5.

Jinlong Wang, Xiaojun Liang, Liming Wang, Attribute Data Analysis (2nd edition). Higher Education Press, 2013.7

Lingling Guan, Attribute Data Analysis Based on SAS (1st edition). China Statistics Press, 2014.8.

Xilai Shi, Introduction to Attribute Data Analysis (1st edition). Peking University press, 2006.1.

Course Assessment

Course Schedule