Advanced Research Methods: Course Description
Advanced Research Methods: Course Description
Advanced Research Methods: Course Description
COM6315 Section 05CE
Spring 2015
Course Description
This course is designed to provide graduate students with an advanced understanding of the principles, methods, and
techniques of quantitative research. Specifically, this course aims to help students to understand methods and analyses
that are frequently used in communication research and to gain fundamental knowledge and practical skills necessary to
conduct statistical analyses and interpret the results.
The course consists of two main parts. The first part of the course covers key concepts related to quantitative research
methods. The purpose is to help students to understand and critically analyze the method and design of quantitative
research published in academic and non-academic journals. The second part of the course covers a range of statistical
analyses commonly used in communication research. The emphasis is placed on obtaining practical skills in performing
statistical analyses using SPSS, reading the output, interpreting and writing up the results in a manuscript form.
Course Objectives
At the conclusion of the course, students should be able to:
1. Critically appraise the method and design of quantitative research in a published article.
2. Identify an appropriate quantitative method and analysis for a given research question and/or hypothesis.
3. Understand types and nature of quantitative measurement as well as means to evaluate reliability and validity of
the measurement.
4. Understand characteristics, purposes, and indices of key statistical analyses.
5. Perform statistical analyses using SPSS and read the output.
6. Summarize and interpret the results of analysis in a manuscript form.
Course Requirement
Students must have access to SPSS.
Course Readings
Required:
Mertler, C. A., & Vannatta, R. A. (2010). Advanced and multivariate statistical methods (5th ed.). Glendale, CA:
Pyrczak Publishing.
Frey, L. R., Botan, C. H., & Kreps, G. L. (2000). Investigating communication: An introduction to research
methods (2nd ed.). Needham Heights, MA: Allyn & Bacon. [Reserved in Library West]
Pallant, J. (2011). SPSS survival manual: A step-by-step guide to data analysis using SPSS (4th ed.). Crows Nest, N.S.W.,
Australia: Allen & Unwin. [eBook available on Course Reserves on Sakai]
Recommended Optional:
In addition to the above required books, I use the following references to prepare my lectures. A few chapters of Blue
Book series are available on the E-Learning course site. Students are encouraged to download other chapters relevant to
the course topics. Hair et al.’s book covers topics of multivariate analyses comprehensively and is a useful reference for
your own research as well as for this course.
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Blue Book series by Statistical Associates Publishing at http://www.statisticalassociates.com/booklist.htm
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Upper Saddle
River, NJ: Prentice Hall. [Reserved in Library West]
Course Content
This course consists of the following nine modules.
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Module 8: Factor Analysis
This module begins with an introduction of exploratory factor analysis (EFA) and confirmatory factor analysis
(CFA). After the introduction, the module focuses on EFA and a particular extraction technique of EFA. It also
covers indices of factor analysis and rotation methods. Finally, it describes a procedure of conducting an EFA in
SPSS, reading the SPSS output, and summarizing the results.
Assignments
The assignments of this course are designed for students to apply the knowledge gained from the lecture in hands-on
exercises. Specifically, students review published empirical research critically on its method, analysis, and results.
Students also conduct statistical analyses using SPSS and write up the results in a manuscript form.
All assignments must be word-processed and follow the assignment format rules and file naming convention (see
below). Pay close attention to the page limit of each assignment. A penalty is applied for each line that exceeds the page
limit. Assignments are due to Sakai E-Learning. Refer to the Course Schedule for deadlines.
You have an option of choosing an article(s) in your field of study, which employed the statistical analysis (analyses)
relevant to the assignment. The article must contain all of necessary information to complete the assignment.
Submit the article (via email) at least two weeks before the assignment deadline for my review and approval.
Articles submitted within two weeks of the assignment deadline will not be reviewed and cannot be used for the
assignment.
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variable and a short description of variable measurement (e.g., how it was measured), and (d) relationships of
variables examined with the test. The assignment must not exceed 3 pages.
Assignment 6: Two-Way ANOVA, One-Way Repeated Measures ANOVA, and One-Way or Two-Way
ANCOVA
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Conduct a two-way ANOVA, one-way repeated measures ANOVA, and one-way or two-way ANCOVA and
report the results as specified above (page limit: 5)
Assignment Format
Word documents (.doc or docx) must be formatted to have a 1” margin on all four sides. Use 12-point Times New
Roman font (a larger font can be used for titles and headings) and insert page numbers at bottom center. Use one
font style only including page numbers (i.e., Times New Roman). The document must be left justified and prepared
according to the APA style.
At the top of the first page, indicate 1) module number and title (e.g., Module 1. Types of Quantitative Research
Method), 2) assignment title (e.g., Assignment 1: Types of Quantitative Research Method), 3) course title and
semester (e.g., Advanced Research Methods, Fall 2014), 4) date of submission, and 5) student name. Do not use a
cover page unless otherwise instructed.
The purpose of results tables is to help the reader to understand the results of the analysis easily. Keep that in mind
when constructing results tables. For instance, do not split a table over two pages. If a table is too large to place in
the remainder of the page, use a page break and place it in the next page so that the entire table can fit in a page.
For Word documents and SPSS outputs: module number_assignment number_student name (e.g., Module
1_Assignment 1_Hyojin Kim.docx, Module 3_Assignment 4_Hyojin Kim.spv)
Quizzes
A total of five quizzes are given in the course and can be found in the Assessments tool on Sakai. Quizzes are based on
lecture videos and required readings. Do not solely rely on lecture videos to study for a quiz, although lecture videos
can be used as a guide to understand important topics to focus on. Quizzes are timed and graded immediately following
completion.
Final Exam
The final exam will be given in Week 15 and due by Apr 22nd noon. Students will be given one week to complete the
exam. Questions ask students to review and critically analyze the method, data analysis, and results of assigned journal
articles; and read SPSS outputs, interpret, and write up the results. Students must submit a Word file containing their
answers. The Word document must conform to the assignment format rules and file naming convention (e.g., Final
Exam_Hyojin Kim.docx).
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Grading Criteria & Scale
No extra credit projects are available. All assignments and quizzes are due on the specified dates (refer to the Course
Schedule). Twenty percent of the assignment’s grade will be deducted each day the assignment is turned in late. All
assignments must be prepared and presented professionally and proof-read thoroughly. Students must take special care
to use proper words and spelling, grammatically correct sentences, and logically flowing content. A penalty is applied
for each misspelled word, grammatically incorrect sentences and other writing errors after three errors.
http://www.indiana.edu/~wts/wts/plagiarism.html
http://www.sja.ucdavis.edu/sja/plagiarism.html
The students of the University of Florida recognize that academic honesty and integrity are fundamental values of the
University community. Students who enroll at the University commit to holding themselves and their peers to the high
standard of honor required by the Honor Code. Any individual who becomes aware of a violation of the Honor Code is
bound by honor to take corrective action. A student-run Honor Court and faculty support are crucial to the success of
the Honor Code. The quality of a University of Florida education is dependent upon the community acceptance and
enforcement of the Honor Code.
Students are strongly advised to view UF’s academic honesty guidelines at:
http://www.dso.ufl.edu/judicial/procedures/honestybrochure.php
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Course Schedule
The following is a tentative course schedule. Additional lecture videos and readings may be added. The quizzes are accessible in the Assessments
tool on the course site of Sakai E-Learning. Assignments must be submitted to the Assignments tool on Sakai.
Week 1 & 2 Module 1: Types of Quantitative Research Method
Jan 6 – Jan 16 Required Reading Frey, Botan, & Kreps: Ch. 7
Optional Reading Research Methods Knowledge Base: http://www.socialresearchmethods.net/kb/design.php
Lecture Video Welcome (Course Materials homepage)
1.1: Overview of Quantitative Research
1.2: True Experiment
1.3: Threats to Validity
1.4: Quasi Experiment
1.5: Non-Experimental Research
Quiz Take Quiz 1 (covers the syllabus and Welcome video) in Assessments by Jan 9th noon
Take Quiz 2 (Module 1) in Assessments by Jan 16th noon
Assignment Answer the questions on Discussion board to introduce yourself to the class by Jan 9th noon
Submit Assignment 1 to Assignments by Jan 16th noon
Week 3 Module 2: Conceptualization & Operationalization
Jan 19 – Jan 23 Required Reading Kerlinger: Ch. 3 (Available on Sakai E-Learning)
Pedhazur & Schmelkin: pp. 54-59 (Available on Sakai E-Learning)
Lecture Video 2.1: Theory, Hypothesis, & Research Questions
2.2: Constructs & Variables
2.3: Indicators
Quiz Take Quiz 3 (Module 2) in Assessments by Jan 23rd noon
Assignment Submit Assignment 2 to Assignments by Jan 23rd noon
Week 4 Module 3: Measurement, Reliability, & Validity
Jan 26 – Jan 30 Required Reading Frey, Botan, & Kreps: Ch. 4 (pp. 81-95), 5 (pp. 109-119)
Optional Reading Blue Book: Measurement Levels, Scales & Measures, Validity & Reliability
Lecture Video 3.1: Overview of Measurement
3.2: Levels of Measurement
3.3: Other Important Topics of Measurement
3.4: Reliability
3.5 Validity
Quiz Take Quiz 4 (Module 3) in Assessments by Jan 30th noon
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Week 5 & 6 Module 4: Basic Statistics
Feb 2 – Feb 13 Required Reading Frey, Botan, & Kreps: Ch. 11 (pp. 289-301, 305-307), 12
Mertler & Vannatta: Ch. 1, 2
Pallant: Ch. 6, 8-12
Optional Reading Blue Book: Correlation
Lecture Video 4.1: Descriptive Statistics
4.2: Dispersion
4.3: Test of Significance
4.4: Basic Inferential Statistics
4.5a-c: Data Analysis and Interpretation using SPSS
Quiz Take Quiz 5 (Module 4) in Assessments by Feb 6th noon
Assignment Submit Assignments 3 and 4 to Assignments by Feb 13th noon
Week 7 & 8 Module 5: ANOVA & ANCOVA
Feb 16 – Feb 27 Required Reading Mertler & Vannatta: Ch. 4-5
Pallant: Ch. 18-20, 22
Optional Reading Blue Book: GLM Univariate
Lecture Video 5.1: F-test, One-Way ANOVA, & Post-Hoc Test
5.2: Two-Way ANOVA & Repeated Measures ANOVA
5.3: ANCOVA
5.4a-c: Data Analysis and Interpretation using SPSS
Assignment Submit Assignments 5 and 6 to Assignments by Feb 27th noon
Week 9 Spring Break
Week 10 Module 6: MANOVA & MANCOVA
Mar 9 – Mar 13 Required Reading Mertler & Vannatta: Ch. 6
Pallant: Ch. 21
Optional Reading Blue Book: GLM Multivariate
Lecture Video 6.1: Multivariate Analysis
6.2: MANOVA & MANCOVA
6.3a-b: Data Analysis and Interpretation using SPSS
Assignment Submit Assignments 7 and 8 to Assignments by Mar 13th noon
Week 11 Module 7: Regression
Mar 16 – Mar 20 Required Reading Mertler & Vannatta: Ch. 7
Pallant: Ch. 13
Optional Reading Blue Book: Multiple Regression
Lecture Video 7.1: Overview of Regression Analysis
7.2: Multiple Regression
7.3: Other Important Topics of Multiple Regression
7.4a-b: Data Analysis and Interpretation using SPSS
Assignment Submit Assignments 9 and 10 to Assignments by Mar 20th noon
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Week 12 Module 8: Factor Analysis
Mar 23 – Mar 27 Required Reading Mertler & Vannatta: Ch. 9
Pallant: Ch. 15
Optional Reading Blue Book: Factor Analysis
Lecture Video 8.1: Factor Analysis
8.2: Data Analysis and Interpretation using SPSS
Assignment Submit Assignments 11 and 12 to Assignments by Mar 27th noon
Week 13 Module 9: Logistic Regression
Mar 30 – Apr 3 Required Reading Mertler & Vannatta: Ch. 11
Pallant: Ch. 14
Optional Reading Blue Book: Logistic Regression
Lecture Video 9.1: Logistic Regression
9.2: Data Analysis and Interpretation using SPSS
Assignment Submit Assignments 13 and 14 to Assignments by Apr 3rd noon
Week 14 Module 10: TBA
Apr 6 – Apr 10 The module topic, reading, and assignments will be announced later. Assignments given for this module will be due to Assignments by
Apr 10th noon
Week 15 & 16 Wrap-up & Final Exam
Apr 13 – Apr 22 Submit the Final Exam to Assignments by Apr 22nd noon