Week 1 (2/17)  Introduction  Hours spent in class  Hours spent outside class  Week 2 (2/24)  First encounter with the data
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 2)
Discussion topics:
 Get to know SPSS: data view and variable view; language
 How to enter data—practicing data entry
 How to define different columns?
 What is a variable? Understanding different levels of measurement
 How to “describe” a variable: central tendency and percentage
 3  3  Week 3 (3/2)  Understanding variability
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 3)
Discussion topics:
 How to download a secondary dataset
 Understanding the correspondence between concepts and variables
 3  3  Week 4 (3/9)  Probability and sampling distribution
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 8)
Discussion topics:
 What is probability?
 Is your data distribution “normal?”
 What is Z score?
 Central Limit Theorem (CLT)
 3  3  Week 5 (3/16)  Hypothesis testing (of means)
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 7 & 9)
Discussion topics:
 Null vs alternative hypothesis
 Critical value and region
 Confidence interval
 3  3  Week 6 (3/23)  Comparison of means for two groups
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 10 & 11)
 3  3  Week 7 (3/30)  Comparison of means for more than two groups
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 13)
Discussion topics:
 F test
 ANOVA
 Posthoc test
Presentation (1):
 Scheufele, D. A., Kim, E., & Brossard, D. (2007). My Friend's Enemy: How SplitScreen Debate Coverage Influences Evaluation of Presidential Debates. Communication Research, 34(1), 324.
 Feldman, L., & Hart, P. S. (2016). Using Political Efficacy Messages to Increase Climate Activism The Mediating Role of Emotions. Science Communication, 38(1), 99127.
 3  3  Week 8 (4/6)  Building scales, validity, and reliability test
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 6)
 Babbie, E. (2007). The practice of social research (11th ed.). Belmont, CA: Wadsworth. (Chap 6: Indexes, scales, and typologies, Recommended).
Discussion topics:
 Summative/averaged scales in SPSS (problems with missing values, scale ranges, etc.)
 Reliability test in SPSS
 Different approaches to test validity of a scale
 Validity test in SPSS
 3  3  Week 9
(4/13)  Association of continuous variables—correlation & regression analysis
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 15 & 16)
Discussion topics:
 Interpretation of outputs
 Presentation of data—tables
Presentations (2):
 Cho, J. (2013). Campaign tone, political affect, and communicative engagement. Journal of Communication, 63(6), 11301152.
 3  3  Week 10
(4/20)  Hierarchical linear regression
Discussion topics:
 Different types of betas
 The idea of “control”
 R square change
 How to report hierarchical regressions
Presentations (3):
 Lee, C.J., & Scheufele, D. A. (2006). The influence of knowledge and deference toward scientific authority: A media effects model for public attitudes toward nanotechnology Journalism & Mass Communication Quarterly, 83(4), 819834.
 3  3  Week 11
(4/27)  Mediation
Discussion topics:
 What is mediation?
 How to run mediation models in SPSS?
Presentations (4):
 Shih, T.J., & Lin, C.Y. (2017). Developing communication strategies for mitigating actions against global warming: Linking framing and a dual processing model. Environmental Communication, 119.
 3  3  Week 12
(5/4)  Interactions
Discussion topics:
 What is interaction?
 How to create interaction terms?
 How to run models with interactions in SPSS?
 Where to find relevant statistics in SPSS output?
 How to make an interaction figure?
Presentations (5):
 Brossard, D., Scheufele, D., Kim, E., & Lewenstein, B. V. (2009). Religiosity as a perceptual filter: examining processes of opinion formation about nanotechnology. Public Understanding of Science, 18(5), 646558.
 3  3  Week 13 (5/11)  More complicated models—moderated mediation
Discussion topics:
 What is moderated mediation or mediated moderation?
 What are some possible models?
 How to run these models and interpret the results?
****Discussion of final paper (1 or 2 pages outline due)
 3  3  Week 14 (5/18)  Association of categorical variables
Readings:
 Salkind, N. J. (2010). Statistics for people who (think they) hate statistics. Thousand Oaks, California: Sage Publications, Inc. (Chap 17)
Discussion topics:
 Content analysis
 χ^{2 }test
 3  3  Week 15 (5/25)  彈性授課1: Working week (No class)
  3  Week 16 (6/1)  Final paper presentation
 3  3  Week 17 (6/8)  彈性授課2: Working week (No class)
***Method and result section draft due before midnight
  3  Week 18 (6/15)  彈性授課3: Final paper is due at 5:00pm.   3 

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 6point 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 takehome 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 highquality 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 12point 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.
