教學大綱 Syllabus

科目名稱:傳播統計分析

Course Name: Statistics in Communication

修別:選

Type of Credit: Elective

3.0

學分數

Credit(s)

17

預收人數

Number of Students

課程資料Course Details

課程簡介Course Description

This is a course which focuses both on the introduction of statistical concepts and the application of statistical techniques. The class will cover topics ranging from descriptive statistics to inferential statistics, including regression analysis.

核心能力分析圖 Core Competence Analysis Chart

能力項目說明


    課程目標與學習成效Course Objectives & Learning Outcomes

    The goal of this course is twofold—(1) to introduce basic statistical techniques and (2) to equip students with the ability to apply these techniques in various research settings, including survey, experiments, and content analysis. This class will also teach you how to perform real analysis using SPSS and how to make sense of outputs. Ultimately, it is hoped that by taking this class you will be able to develop a study from scratch and finish it as a full paper.

    每周課程進度與作業要求 Course Schedule & Requirements

    Week 1 (2/14)

    Introduction

    Week 2 (2/21) 

    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 (2/28)

    Holiday

    Week 4 (3/7)

    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 5 (3/14)

    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 6 (3/21)

    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 7 (3/28)

    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 8 (4/4)  

    Holiday

    Week 9 (4/11) 

     

    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 10 (4/18)

     

    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 11 (4/25)

     

    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 12 (5/2)

     

    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 13 (5/9)

    Mediation

     

    Discussion topics:

    • What is mediation?
    • How to run mediation models in SPSS?
    • Andrew Hayes’ SPSS macro

     

    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 14 (5/16)

    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 15 (5/23)

    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

     

     

    Week 16 (5/30)

     

    Working week 1 (No class) ***Method section draft due by midnight

     

    Week 17 (6/6)

     

    Working week 2 (No class)

     

    Week 18 (6/13)

     

    Final paper is due by midnight

     

     

    授課方式Teaching Approach

    30%

    講述 Lecture

    20%

    討論 Discussion

    20%

    小組活動 Group activity

    30%

    數位學習 E-learning

    0%

    其他: Others:

    評量工具與策略、評分標準成效Evaluation Criteria

    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.

    指定/參考書目Textbook & References

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