Quantitative Methods for Communication (Spring 2022)

From CommunityData

Course Information

COM 304: Quantitative Methods for Communication Research

Lecture

Location: LWSN 1142
Class Hours: Tuesdays and Thursdays; 9:30-10:20 AM

Recitations

Location: BRNG B286
Section 002: 1:30-2:20 PM F, with Yihan Jia
Section 003: 12:30-1:20 PM F, with Grace Lee
Section 006: 11:30-12:20 PM F, with Grace Lee
Section 007: 2:30-3:20 PM F, with Yihan Jia

Instructors

Professor: Jeremy Foote
Email: jdfoote@purdue.edu
Office Hours: Thursdays; 2:00–4:00pm and by appointment
Graduate TA: Grace Lee
Email: lee3416@purdue.edu
Graduate TA: Yihan Jia
Email: jia110@purdue.edu

Course Overview and Learning Objectives

Welcome to COM 304: Quantitative Methods for Communication! We are excited to have you in the class. Nearly all communication jobs involve quantitative research in some way; in this course, we will provide you a foundation for doing quantitative communication research.

I know that for many Communication majors even thinking of math and statistics is traumatic, but we will work hard to provide the resources that you need to succeed and we will take things one step at a time. You can do this!


This course introduces students to a range of social-scientific research methods used to investigate human communication. By the end of this course, you will be able to:

  1. Explain the types of research questions, methods, and analyses used by scholars who conduct social-scientific studies of communication, as well as by practitioners in fields such as marketing and consumer research, political polling, etc.;
  2. Critically evaluate quantitative research reports, including those you may read in other courses at Purdue as well as those described in the popular media, appearing in business reports, grant applications, and so forth;
  3. Design and conduct basic research studies about communication-related topics.

The course is organized into three components which are addressed simultaneously throughout the semester: (1) Research Design, (2) Statistics, and (3) Statistical Software.

The Research Design component focuses on the process of planning research, considering the range of choices researchers must make in order to conduct useful studies. This component will not only help you conduct research, it will make you a more critical research consumer.

The Statistics component is concerned with analyses by which numerical data can be synthesized, described, and interpreted. This component provides a strong conceptual introduction to statistics—with a limited amount of math—and will help you to be confident in analyzing basic numerical data for almost any purpose.

The Software component is closely allied with the Statistics component. This component focuses on basic applications of the Statistics Package for the Social Sciences (SPSS)—a powerful, but user-friendly computer program—and will give you an immediately marketable skill (something to put on the resume). This course should be of use to students with a number of goals, including those: (a) who are contemplating graduate study in communication or related fields; (b) whose current or future career may require them to answer questions by collecting and analyzing data (e.g., advertising, human relations, marketing, public relations); and (c) who want to develop their skills at critically evaluating research and knowledge claims made by “experts” on communication issues.

Required resources and texts

Readings

Required texts:

  • Salkind, N. J. (2017). Statistics for people who (think they) hate statistics (6th ed.). Los Angeles, CA: Sage.
    • Note: I believe that you should be fine with one edition newer or older than this one, too. Just make sure that the topic matches up with what the syllabus says.

You also will be assigned readings from online resources; these readings are listed on the course schedule of this syllabus (below) and links are provided in each lecture’s folder on the course Brightspace site. Readings from the text and online resources will be covered in the midterm and final exams.

Technology

Smart phone or laptop to complete in-class Hotseat participation questions.


We will be using the statistical software SPSS for most of the labs. SPSS is loaded on all Purdue lab computers. In a pinch, you may be able to access it via goremote (https://goremote.itap.purdue.edu) but in general using the lab computers will be simpler and faster.

Course logistics

Note About This Syllabus

Although the core expectations for this class are fixed, this is my first time teaching the course and I may make some adjustments to the details of readings and assignments. As a result, there are three important things to keep in mind:

  1. Although details on this syllabus will change, I will not change readings or assignments less than one week before they are due. If you plan to read more than one week ahead, contact me first.
  2. Because this a wiki, you will be able to track every change by clicking the history button on this page. I will also summarize these changes in an announcement on Brightspace that should be emailed to everybody in the class if you have notifications turned on.
  3. I will ask the class for voluntary anonymous feedback. Please let me know what is working and what can be improved.

Class Sessions

There are two types of class sessions: lecture sessions and lab sessions.

The lectures sections will be led by Dr. Foote and will be Tuesdays and Thursdays in Lawson 1142. The lab sessions will be on Fridays and will be led by Grace and Yihan, the TAs of the course.

I expect you to come to the lecture sessions prepared, having read the material. It is fine to have questions---indeed, one of the goals of these sessions is to identify things that are confusing and to clear up misconceptions---but you should be ready to talk about your attempts to understand and why something is confusing.

I will do my best to post lecture slides to Brightspace before class.

Getting Help

Your first place to look for help should be each other. By asking and answering questions on Discord, you will not only help to build a repository of shared information, but to reinforce our learning community.

I will also hold office hours on Thursdays, from 2-4 (sign up here).

I will also check Discord at least once a day. I encourage you to post questions there, and to use it as a space where we can help and instruct each other. In general, you should contact me there. I am also available by email. You can reach me at jdfoote@purdue.edu. I try hard to maintain a boundary between work and home and I typically respond only on weekdays during business hours.


Assignments

There will be multiple types of assignments, designed to encourage learning in different ways.

Participation

I expect you to be an active member of our class. This includes paying attention in class, participating in activities, and being actively engaged in learning, thinking about, and trying to understand the material.

To make sure that everyone has an opportunity to participate and to encourage you to do the assignments, I will randomly select students to answer questions about the concepts from readings or to explain portions of homework assignments and labs.

Discussion Questions

In order to make sure that we are prepared to have a productive discussion, you are required to submit one or two discussion questions that you think would be interesting to discuss on Monday by noon. Post your questions on the shared Google Doc at https://docs.google.com/document/d/1AK4MhWLVwDuxqvTwLomN7hu4aLpo59n5qXgEap8SBNc/edit?usp=sharing; try to group similar questions together.

Questions should engage with the readings and either connect to other concepts or to the "real world". Here are some good example questions:

  • The readings this week talked a lot about how network ties get created. I made a list of my closest friends and I realized that most of them only became friends after we happened to be in the same groups over and over again. What role does repetition have in forming ties?
  • I was confused by the reading on social capital. What's the difference between social capital and power? And if they are the same, then why not just call it "network power"?
  • Imagine you were asked to analyze the network of a big company to help them to identify people who deserve a raise. What measures would you use to identify them? What would you not use?

Some weeks will also include more practical homework (mostly data manipulation and visualization in R). On those weeks, portions of our discussions will center around going over homework questions and identifying places where folks are still confused.

Homework/Labs

There will be a number of homework assignments. At the beginning of the class, these will be designed to help you to grasp foundational network concepts. As the class progresses, more and more of them will be analyzing and visualizing networks in R.

Exams

There will be one take home exam. It will assess your understanding of core communication and social networks concepts.

Final Project

Students will work on a Final Project that explains how network analysis and a network approach can benefit an organization.

A number of intermediate assignments through the semester will help you to gain the skills and data necessary to be successful.

Grades

This course will follow a "self-assessment" philosophy. I am more interested in helping you to learn things that will be useful to you than in assigning grades. In general, I think that my time is much better spent in providing better feedback and in being available to work through problems together.

The university still requires grades, so you will be leading the evaluation of your work. This will be completed with me in three stages, at the end of weeks 5, 10, and 16. In each stage, you will use this form to reflect on what you have accomplished thus far, how it has met, not met, or exceeded expectations, based both on rubrics and personal goals and objectives. At each of these stages you will receive feedback on your assessments. By the end of the semester, you should have a clear vision of your accomplishments and growth, which you will turn into a grade. As the instructor-of-record, I maintain the right to disagree with your assessment and alter grades as I see fit, but any time that I do this it will be accompanied by an explanation and discussion. These personal assessments, reflecting both honest and meaningful reflection of your work will be the most important factor in final grades.

We will use the following rubric in our assessment:

  • 20%: class participation, including attendance and participation in discussions and group work
  • 20%: Labs and homework assignments
  • 25%: Exam
  • 35%: Final Project

The exam will be graded like a normal exam and the score will make up 25% of your grade. For the rest of the assignments (and the other 75% of your grade), I will provide feedback which will inform an ongoing conversation about your work.

My interpretation of grade levels (A, B, C, D/F) is the following:


A: Reflects work the exceeds expectations on multiple fronts and to a great degree. Students reaching this level of achievement will:

  • Do what it takes to learn the principles and techniques of social networks, including looking to outside sources if necessary.
  • Engage thoughtfully with an ambitious final project.
  • Take intellectual risks, offering interpretations based on synthesizing material and asking for feedback from peers.
  • Share work early allowing extra time for engagement with others.
  • Write reflections that grapple meaningfully with lessons learned as well as challenges.
  • Complete all or nearly all homework assignments at a high level.

B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:

  • Be more safe or consistent than the work described above.
  • Ask meaningful questions of peers and engage them in fruitful discussion.
  • Exceed requirements, but in fairly straightforward ways - e.g., an additional post in discussion every week.
  • Compose complete and sufficiently detailed reflections.
  • Complete many of the homework assignments.

C: This reflects meeting the minimum expectations of the course. Students reaching this level of achievement will:

  • Turn in and complete the final project on time.
  • Be collegial and continue discussion, through asking simple or limited questions.
  • Compose reflections with straightforward and easily manageable goals and/or avoid discussions of challenges.
  • Not complete homework assignments or turn some in in a hasty or incomplete manner.

D/F: These are reserved for cases in which students do not complete work or participate. Students may also be impeding the ability of others to learn.

Extra Credit for Participating in Research Studies

If you feel like you need to earn extra credit in order to earn the grade that you would like, the course is signed up for extra credit through the Brian Lamb School of Communication Research Participation System.

Schedule

NOTE This section may be modified throughout the course to meet the class's needs. Check back in weekly.


Week 1: Variables, Research Questions, and Hypotheses

January 11

Assignment Due:

Required Readings:

  • None

Concepts:

  • Class overview and expectations — We'll walk through this syllabus.
  • Goals of Quantitative Research


January 13

Assignment Due:

  • Read the entire syllabus (this document)

Readings:


Class Schedule:


January 14

Lab 1

Week 2: Surveys

January 18

Assignment Due:


Readings (before class):


Concepts:


January 20

Readings (before class):


Concepts:

January 21

Week 3: Descriptive Statistics

January 25

Readings (before class):


Concepts:

January 27

Readings (before class):


Concepts:

January 28

Lab 3


Week 4: Z-scores and correlation

February 1

Readings (before class):


Concepts:

February 3

Readings (before class):


Concepts:

February 4

Lab 4

Week 5: Reliability and Validity

February 8

Readings (before class):


Concepts:

February 10

Readings (before class):


Concepts:

February 11

Lab 5: Scatterplots and correlation


Week 6: Sampling

February 15

Readings (before class):


Concepts:


February 17

Review for Midterm


February 18

Lab 6: Reliability and Cronbach's alpha


Week 7: Experimental Design

February 22

MIDTERM EXAM


February 24

Readings (before class):


Concepts:

February 25

Lab 7: Review for SPSS Quiz 1

Week 8: Causality

March 1

Readings (before class):


Concepts:

March 3

Readings (before class):


Concepts:

March 4

Lab 8: SPSS Quiz 1


Week 9: Central Limit Theorem and standard errors

March 8

Readings (before class):


Concepts:

March 10

Readings (before class):


Concepts:

March 11

Lab 9

SPRING BREAK MARCH 14-18

Week 10: Testing hypotheses

March 22

Readings (before class):


Concepts:


March 24

Readings (before class):


Concepts:


March 25

Week 11: Significance tests

March 29

Readings (before class):


Concepts:

March 31

Readings (before class):


Concepts:

April 1

Week 12: t-tests

April 5

Readings (before class):


Concepts:

April 7

Readings (before class):


Concepts:

April 8

Week 13: Errors and Ethics

April 12

Readings (before class):


Concepts:

April 14

Readings (before class):


Concepts:


April 15

Week 14-15: Final Project

Week 16: Final Exam

Policies

Attendance

I try very hard to make our meeting times valuable to you and I expect that you attend. That being said, we are in the midst of a pandemic, so if you feel sick or think that you might have COVID, please do not come to class. If you need to miss class, then it is your responsibility to seek out support from classmates for notes, handouts, and other information.

Only I can excuse a student from a course requirement or responsibility. When conflicts can be anticipated, such as for many University-sponsored activities and religious observations, please inform me of the situation as far in advance as possible. For unanticipated or emergency conflicts, when advance notification is not possible, contact me as soon as possible on Discord or by email. In cases of bereavement, quarantine, or isolation, the student or the student’s representative should contact the Office of the Dean of Students via email or phone at 765-494-1747. Our course on Brightspace includes a link to the Dean of Students under 'Campus Resources.'

Classroom Discussions and Peer Feedback

Throughout the course, you may receive, read, collaborate, and/or comment on classmates’ work. These assignments are for class use only. You may not share them with anybody outside of class without explicit written permission from the document’s author and pertaining to the specific piece.

It is essential to the success of this class that all participants feel comfortable discussing questions, thoughts, ideas, fears, reservations, apprehensions and confusion. Therefore, you may not create any audio or video recordings during class time nor share verbatim comments with those not in class linked to people’s identities unless you get clear and explicit permission. If you want to share general impressions or specifics of in-class discussions with those not in class, please do so without disclosing personal identities or details.


Academic Integrity

While I encourage collaboration, I expect that any work that you submit is your own. Basic guidelines for Purdue students are outlined here but I expect you to be exemplary members of the academic community. Please get in touch if you have any questions or concerns.


Nondiscrimination

I strongly support Purdue's policy of nondiscrimination (below). If you feel like any member of our classroom--including me--is not living up to these principles, then please come and talk to me about it.

Purdue University is committed to maintaining a community which recognizes and values the inherent worth and dignity of every person; fosters tolerance, sensitivity, understanding, and mutual respect among its members; and encourages each individual to strive to reach his or her own potential. In pursuit of its goal of academic excellence, the University seeks to develop and nurture diversity. The University believes that diversity among its many members strengthens the institution, stimulates creativity, promotes the exchange of ideas, and enriches campus life.


Accessibility

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, you are welcome to let me know so that we can discuss options. You are also encouraged to contact the Disability Resource Center at: drc@purdue.edu or by phone: 765-494-1247.


Emergency Preparation

In the event of a major campus emergency, I will update the requirements and deadlines as needed.


Mental Health

If you or someone you know is feeling overwhelmed, depressed, and/or in need of mental health support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at 765-494-6995 during and after hours, on weekends and holidays, or by going to the CAPS office of the second floor of the Purdue University Student Health Center (PUSH) during business hours.


Incompletes

A grade of incomplete (I) will be given only in unusual circumstances. The request must describe the circumstances, along with a proposed timeline for completing the course work. Submitting a request does not ensure that an incomplete grade will be granted. If granted, you will be required to fill out and sign an “Incomplete Contract” form that will be turned in with the course grades. Any requests made after the course is completed will not be considered for an incomplete grade.


Additional Policies

Links to additional Purdue policies are on our Brightspace page. If you have questions about policies please get in touch.