All course information is listed within this syllabus.

FDSC 515: Sensometrics - Applied Multivariate Analysis in Sensory & Food Science (3 credits). The main objective of this course is to allow each student to develop the necessary data analysis skills needed for analyzing and interpreting sensory and consumer data.

Prerequisite: STAT 500 (or other) or consent of the instructor.


Instructor for FDSC 515

Dr. Helene Hopfer
Assistant Professor of Food Science
Rasmussen Career Development Professor in Food Science
Program Chair, Graduate Certificate Sensory & Consumer Science

Department of Food Science
218 Rodney A. Erickson Food Science Building
University Park, PA 16802

Office Phone: 814-863-5572
E-mail: Use Canvas Inbox or

Office Hours: By appointment

Course Objectives

Upon completion of this course, you will be able to:

  1. use statistical software to analyze sensory data sets with uni-and multivariate methods
  2. create code to import, analyze, and plot data
  3. select an appropriate data analysis method to answer a research question
  4. evaluate the quality and interpret the results of statistical analyses to answer a research question
  5. explain and write about the results of the data analysis in a scientific report
  6. critically evaluate scientific literature for their experimental design and used statistical methods
  7. lead and guide a discussion on scientific literature
  8. experience how statistical methods are used for sensory data sets

Course Outline

Module 1: Intro to R
Module 2: Working With Data
Module 3: Experimental Design & (M)ANOVA
Module 4: Power Analysis & Missing Data
Module 5: Principal Component Analysis (PCA)
Module 6: Correspondence Analysis
Module 7: Multidimensional Scaling (MDS) & DISTATIS
Module 8: Multi-Factor Analysis (MFA) & Generalized Procrustes Analysis (GPA)
Module 9: Cluster Analysis
Module 10: Discriminant Analysis (CVA)
Module 11: Modeling (PLS)
Module 12: Preference Mapping (IPM, EPM)
Module 13: Conjoint Analysis & Consumer Segmentation
Module 14: New Approaches in Sensometrics

Course Schedule

For due dates, refer to your Syllabus and Calendar within Canvas.

Course Materials

No required text, but useful books can be found on the Further Readings page in Canvas.


Your grade in this course consists of 4 parts:

  1. Pre-lecture code quiz (10% of your grade)
  2. Homework assignments (10% of your grade)
  3. Milestone assignments (30% of your grade)
  4. Literature discussions (20% of your grade)
  5. Take-home final (30% of your grade)
    • You will analyze a data set using the techniques studied in the course (see below). The due date for the final is Friday, May 3rd at 5 p.m. I encourage you to analyze your own data, However, if you would like to analyze your own data for the final, I need to approve the data set by at the latest April 1st, in writing!

Code Quiz (10% of your grade)

To help you with the coding for the homework assignments there will be a coding review and interpretation every week. To prepare for this code review class I will provide a data set and a R code script file on Canvas, together with an online quiz (graded).

Homework Assignments (10% of your grade)

To prepare you for your 4 milestone assignments and your take-home final, there will be weekly homework assignments that are peer-reviewed. You are expected to create code to analyze, and interpret the results for data sets assigned for each topic. The code and interpretation will be reviewed by one of you peers, using a grading rubric.

The purpose is to provide you with the opportunity to apply your knowledge of the selected data analysis method(s) and to help you master written communication of statistical analysis results. You are expected to submit your R code and a 1-page summary of your interpretation for peer-review. Your code needs to run on somebody's computer, be understandable to that person (so use the comment function extensively), and your interpretation needs to make sense and be supported by the data. You may include a graph or table in support of your interpretation, but you also need to ensure that your report covers the major findings of your analysis.

Milestone Assignments (30% of your grade)

At the end of each milestone, there will be a graded assignment where you are expected to demonstrate the skills you learned about in the weeks before. You are expected to create code, analyze, interpret, and report your findings in a report for the assigned data set. These assignments will build upon your weekly homework assignments.

The purpose of the milestone assignments is to provide you with the opportunity to apply your knowledge of the selected data analysis technique(s) and to help you master written communication of these methods.

Unless otherwise noted, your report should include:

  • a description of the data set
  • a description of the statistical method(s) used
  • table(s) and/or graphs of the analysis results
  • a full narrative interpretation of the results using the GEE principles
  • suggested further analyses, if needed, to further explain what is going on with the data
  • statistical program commands (R script)

Each homework is limited to 5 pages, double-spaced, 12-point Arial with 1" margins; statistical program commands should be commented for ease of understanding.

Reports and R code files need to be uploaded to Canvas by the deadline. Acceptable file formats are .pdf for the report and .r for the R scripts, so make sure you are uploading the correct files.

All uploaded files need to be named in the following way:

Report: LastName_HW#.pdf where # is replaced with the homework number.
R script file: LastName_HW#.r

Literature Discussions (20% of your grade)

In order to further your critical thinking skills we are using online discussions for the weekly paper and general bigger picture questions. Participation is a requirement for this course, and the Piazza platform will be used for online discussion about class topics.

My goals for using Piazza are:

  1. to critically evaluate the discussion papers with regards to the s of the study, the methods used, the results and conclusions (e.g., used statistical methods, experimental design, data analysis plan)
  2. to provide a platform where we look at the bigger picture, e.g., how does the material covered in the paper relate to the methods we discussed, how could you apply these methods for your own the data, what could be some of the advantages and limitations, which areas you are confused about, etc

In order to receive your points per week, you must post 2 questions and 2 responses relevant to our class subject matter per week. There will be a Sunday 11:59 p.m. deadline for submissions in your community each week.

Take-Home Final (30% of your grade)

For the final you will analyze a larger data set with different techniques that we discussed in class. You can analyze your own data set if you have obtained prior authorization (see above), otherwise, I will provide a data set.

  • You have to develop research questions for the provided data set. Come up with a background story that allows you to develop those research questions for the provided data set.
  • You have to use at least three different methods to analyze the data and you have to justify why you are using each method. That means, tell me how these methods allow you to answer your research questions.
  • You need to hand in a fully written research paper in the form of a journal article. Use the provided word template to write your final paper—I was told this is actually fun to do. You are limited to a maximum of 5 pages (excluding the appendix of your R script).
    • Provide an abstract, introduction, materials & methods, followed by results and discussion and conclusions.
    • Make sure you state your research questions at the end of the introduction.
    • Describe your data set and all statistical methods used in the Materials & Methods section.
    • Place all necessary tables and graphs directly into the document. Use only graphs and/or tables that support your results and discussion. Do not include any tables/graphs just because R provided them!
    • In your conclusion section suggest further analyses if needed.
    • Include your R script as an .r file as an appendix. If you make any changes to the data set outside of you you need to upload that file as well.
  • Acceptable file formats are .pdf for your final report, .csv or .txt for your raw data set if you made any changes to the provided data set or use your own data set, and .r for your R script.
  • Only material uploaded to Canvas by the submission deadline will be used for your final grade.

Late Submission Policy

Based on previous experiences, I developed a late submission policy as follows:

  • Homework assignments build upon each other, therefore, submission of your homework assignments are due as indicated (typically the Wednesday after the module ends). Peer-reviews of the homework assignments are due 1 week after the submission due date.
  • There are 4 milestone submission deadlines throughout the semester: you are expected to submit your report by the listed due date, past that deadline no late submissions will be accepted!
  • The same holds true for the take-home final.

Scheduling Conflicts

I'd be happy to make arrangements for scheduling conflicts, but need to be advised ahead of time. I am happy to discuss how to best to accommodate scheduling conflicts, but strongly encourage you to contact me as early as possible, rather than waiting until a deadline to ask for an accommodation.

Grading Policy

Grading Criteria
Requirement Point Value Weight
Pre-Lecture Code Quiz --- 10%
Homework Assignments --- 10%
Milestone Assignments --- 30%
Literature Discussions --- 20%
Take-Home Final --- 30%
TOTAL: --- 100%
Grading Scheme
Letter Grade Percentage
A 100% – 94%
A- < 94% – 90%
B+ < 90% – 87%
B < 87% – 84%
B- < 84% – 80%
C+ < 80% – 77%
C < 77% – 70%
D < 70% – 60%
F < 60%

Please refer to the University Grading Policy for Graduate Courses for additional information.

NOTE: If you are planning to graduate this semester, please communicate your intent to graduate to your instructor. This will alert your instructor to the need to submit your final grade in time to meet the published graduation deadlines. For more information about graduation policies and deadlines, please see "Graduation" under World Campus Student Resources.

Technical Requirements

This course is offered online and it assumed you possess the minimum system requirements and computing skills to participate effectively. A list of technical requirements is listed on the World Campus' Penn State Technical Requirements page.

Minimum Skills

  • You should have an understanding of basic computer usage (creating folders/directories, switching between programs, formatting and backing up media, accessing the Internet).
  • You must be able to conduct word processing tasks such as creating, editing, saving, and retrieving documents.
  • You must be able to use a web browser to open web pages, download files, and search the Internet.
  • You must be able to use an e-mail program to send and receive messages and to attach and download documents/files.
  • You must be able to download and install programs or plug-ins from the Internet.

Accessibility Information

  • Accessibility statement for Canvas.


The term "Netiquette" refers to the etiquette guidelines for electronic communications, such as e-mail and discussion postings. Netiquette covers not only rules to maintain civility in discussions, but also special guidelines unique to the electronic nature of messages. Please review Virginia Shea's "The Core Rules of Netiquette" for general guidelines that should be followed when communicating in this course.

Support Services

As a World Campus student, you have access to a variety of services and resources, including advising, tutoring, library services, career services, and more. Please visit the World Campus Student Services page for more information.

If you experience technology problems of any kind in Canvas, please select the Help icon and select "Report a Canvas Problem," "Chat with Support," or "Call Support." It is in your own best interest to be as specific as you possibly can. Vague descriptions of a problem only delay assistance. Try to include information such as: the specific course page, quiz question, etc. you were on; what you attempted to do when that failed; the exact language of any error message displayed on your screen; the date and time when your problem occurred; and any other pertinent information (does the problem happen consistently and always in the same way, etc.).

Online Students Use of the Library

As Penn State World Campus students, you have access to many of the materials that the library offers to students. The library website has a lot to offer, but can be overwhelming. A guide has been created to serve as your introduction to important library resources, services, and important pages within the library. The Online Student Library Guide is updated regularly by the online librarian and is intended to provide a level of comfort through an introduction to help you feel comfortable navigating the library website to find valuable information for your coursework.

Penn State Policies

Log-In Policy

Students are expected to log-in regularly to keep up-to-date with announcements, discussions, etc. The class will progress at a regular pace throughout the semester and there are specific due dates and times for assignments, etc.

Course Availability

Your course will be available to you beginning the first day of class for each semester and will remain open for one year. After one year the course will close.

Academic Integrity

Academic integrity is the pursuit of scholarly activity in an open, honest and responsible manner. Academic integrity is a basic guiding principle for all academic activity at The Pennsylvania State University, and all members of the University community are expected to act in accordance with this principle. Consistent with this expectation, students should act with personal integrity, respect other students' dignity, rights, and property, and help create and maintain an environment in which all can succeed through the fruits of their efforts. Academic integrity includes a commitment not to engage in or tolerate acts of falsification, misrepresentation or deception. Such acts of dishonesty violate the fundamental ethical principles of the University community and compromise the worth of work completed by others (see Faculty Senate Policy 49-20, G-9 Procedures and the Code of Conduct).

Read the Academic Integrity Guidelines for the College of Agricultural Sciences

A lack of knowledge or understanding of the University's Academic Integrity policy and the types of actions it prohibits and/or requires does not excuse one from complying with the policy. Penn State and the College of Agricultural Sciences take violations of academic integrity very seriously. Faculty, alumni, staff and fellow students expect each student to uphold the University's standards of academic integrity both inside and outside of the classroom.

Educational Equity Statement

Penn State takes great pride to foster a diverse and inclusive environment for students, faculty, and staff. Acts of intolerance, discrimination, or harassment due to age, ancestry, color, disability, gender, gender identity, national origin, race, religious belief, sexual orientation, or veteran status are not tolerated and can be reported through Educational Equity at the Report Bias webpage.

Privacy Policies

For information about Penn State's privacy statement and what it encompasses, please read their web privacy statement. Visit Penn State's FERPA Guidelines for Faculty and Staff webpage for information regarding its rules on governing the privacy of student educational records.

Copyright Notice

All course materials students receive or to which students have online access are protected by copyright laws. Students may use course materials and make copies for their own use as needed, but unauthorized distribution and/or uploading of materials without the instructor's express permission is strictly prohibited. University Policy AD 40, the University Policy Recording of Classroom Activities and Note Taking Services addresses this issue. Students who engage in the unauthorized distribution of copyrighted materials may be held in violation of the University's Code of Conduct, and/or liable under Federal and State laws.

Counseling and Psychological Services (CAPS)

Many students at Penn State face personal challenges or have psychological needs that may interfere with interfere with their academic progress, social development, or emotional well-being. The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings. These services are provided by staff who welcome all students and embrace a philosophy respectful of clients' cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity and sexual orientation.

  • Counseling and Psychological Services (CAPS): 814-863-0395
  • Penn State Crisis Line (24 hours/7 days/week): 877-229-6400
  • Crisis Text Line (24 hours/7 days/week): Text LIONS to 741741
  • Mental Health Services

Accommodations for Persons with Disabilities

Penn State welcomes students with disabilities into the University's educational programs. Every Penn State campus has an office for students with disabilities. The Student Disability Resources Web site provides contact information for every Penn State campus. For further information, please visit the Student Disability Resources Web site.

In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation. If the documentation supports your request for reasonable accommodations, your campus's disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.

Accommodations for Military Personnel

Veterans and currently serving military personnel and/or spouses with unique circumstances (e.g., upcoming deployments, drill/duty requirements, disabilities, VA appointments, etc.) are welcome and encouraged to communicate these, in advance if possible, to the instructor in the case that special arrangements need to be made.

Use of Trade Names

Where trade names are used, no discrimination is intended and no endorsement by the World Campus, Outreach and Cooperative Extension, the College of Agricultural Sciences, or The Pennsylvania State University is implied.

Subject to Change Statement

Please note that this Course Syllabus is subject to change. Students are responsible for abiding by such changes.