SemesterSpring Semester, 2021
DepartmentCollege of Communication Specialized Subjects for Freshman and Sophomore Majors
Course NameStatistics in Communication
InstructorSHIH TSUNG-JEN
Credit3.0
Course TypeElective
Prerequisite
Course Objective
Course Description
Course Schedule

 















































































Week 1 (2/24)

Introduction

Week 2 (3/3) 



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



 

Week 3 (3/10)



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



 

Week 4 (3/17)

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)



 

Week 5 (3/24)

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



 

Week 6 (3/31)

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)



 

Week 7 (4/7)

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

  • Post-hoc test



 



Reference articles (1):




  • Scheufele, D. A., Kim, E., & Brossard, D. (2007). My Friend's Enemy: How Split-Screen Debate Coverage Influences Evaluation of Presidential Debates. Communication Research, 34(1), 3-24.

  • Feldman, L., & Hart, P. S. (2016). Using Political Efficacy Messages to Increase Climate Activism The Mediating Role of Emotions. Science Communication, 38(1), 99-127.



 

Week 8 (4/14)  

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



 

Week 9 (4/21)  



 

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



 



Reference articles (2):




  • Cho, J. (2013). Campaign tone, political affect, and communicative engagement. Journal of Communication, 63(6), 1130-1152.



Week 10 (4/28)



 

Hierarchical linear regression



 



Discussion topics:




  • Different types of betas

  • The idea of “control”

  • R square change

  • How to report hierarchical regressions



 



Reference articles (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), 819-834.



 

Week 11 (5/5)



 

Mediation



 



Discussion topics:




  • What is mediation?

  • How to run mediation models in SPSS?



 



Reference articles (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, 1-19.



 

Week 12 (5/12)



 

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?



 



Reference articles (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), 646-558.



 



***Final paper outline (idea) due by Midnight



 

Week 13 (5/19)



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

  • χ2 test



 



***Method section draft due before midnight



 

Week 14 (5/26)



彈性授課1: Working week 1 (No class)



 

Week 15 (6/2)

Final paper presentation



 

Week 16 (6/9)

彈性授課2: Working week 2 (No class)



 

Week 17 (6/16)

彈性授課3: Working week 3 (No class)



 

Week 18 (6/23)

Final paper is due at 5:00pm.


 



**This syllabus may be subject to change



 


Teaching Methods
Teaching Assistant
Requirement/Grading

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.


Textbook & Reference
Urls about Course
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