Week 1 Introduction
Week 2 First Encounting with Data
Week 3 Understanding Variability
Week 4 Probability and Sampling Distribution
Week 5 Hypothesis Testing (of means)
Week 6 Comparison of Means for Two Groups
Week 7 Building Scales, Validity, and Reliability Test
Week 8 Exploratory Factor Analysis
Week 9 Comparison of Means for More Than Two Groups
Week 10 Association of Continuous Variables --- Correlation
Week 11 Regression Analysis
Week 12 Hierarchical Linear Regression
Week 13 Interactions
Week 14 Association of Catergorical Variables
Week 15 Final Paper Presentation
Week 16 彈性授課 (term paper consulting)
Week 17 彈性授課 (term paper revision)
Week 18 彈性授課 (term paper submision)
Here is a list of what I expect everyone to achieve in the class. Please be reminded that these requirements are necessary conditions for passing the class; i.e., you are not supposed to miss ANY part of the requirements.
(1) Class attendance and participation (10%):
Although attendance seems to be a very basic requirement, I found some people have problem fulfilling it. As a result, please be reminded that I will pay special attention to attendance and punctuality. Students who missed the class twice will be downgraded 3 points (missing 3 times will result in a 6-point downgrade, etc.). I will also grade your participation in class. It is not enough that you just come to class. You are expected to finish the readings before class and actively discuss the readings or methodological problems.
(2) Assignments (30%)
I will give take-home assignments for practice, which should be printed out and turned in to the instructor in the next class. Late assignments will NOT be accepted.
(3) Literature presentation (10%)
Starting from Week 6, participants of this class are required to select a weekly topic and find one study using that particular statistical approach. Please explain to the class how the statistical method is used in the paper. The presentation is scheduled at the end of the class for about 10 minutes.
(4) Research ideas and drafts (15%)
In order to help you finish your term paper on time, I will ask you to propose a research idea and turn in segments of your paper at different points of time. In particular, the method section is due on Week 13 and the result section on Week 15.
(6) Individual research project (30%)/presentation (5%)
Finally, what you have learned in the class will culminate a FULL research paper of your interest, which should be based on quantitative analysis. Specifically, this will include outlining a problem, translating the problem into research questions and testable hypotheses, developing measures, and providing an analytic answer. Feel free to provide appendices or additional materials to justify your analytic choices or show competing analytic approaches. In order to produce high-quality papers, the data collected by the Taiwan Communication Surveys are recommended. Therefore, the final paper will pretty much be involving secondary data analysis.
All written assignments in this class should be formatted using 12-point font (Arial, Helvetica, or Times New Roman) and double line spacing, and follow APA style (6th version). Please also make sure that all of your assignments live up to minimal professional standards, i.e., are stapled, have cover pages, page numbers, etc.
In addition, each seminar participant is expected to present his or her research paper to the course, including a longer discussion of the methodological and statistical challenges you encountered in your study. Each paper will also be discussed by another participant, similar to a conference presentation. For the presenters, this means that they should share their papers with their discussant at least 48 hours before the presentation. The discussants, in turn, are expected to provide informed and critical feedback. Like all academic discourse, this feedback should be based on evidence and information rather than normative views and opinions.
The final paper is due at 5pm on June 21, 2017. Please upload your paper to our class Web site. Late paper will not be accepted.