VIT_ENOL-526-tom.collins-2024-10-04-09-07-04
Sensometrics of Wines and Spirits
Prefix and Number | VIT_ENOL 526
Semester and Year | Spring 2026
Number of Credit Hours 3
Prerequisites | VIT_ENOL 422, STAT 511, STAT 512
Course Details
Day and Time: TBD
Meeting Location: TBD
Instructor Contact Information
Instructor Name: Dr. Tom Collins
Instructor Contact Information: Wine Science Center
Instructor Office Hours: TBD
Course Description
Sensometrics uses statistical and computational methods to advance the sensory and chemical evaluation of consumer products, wines and spirits specifically in this case. This course will address all aspects of data generation and analysis, including experimental design and methods of sensory evaluation, as well as the use of statistical tools for the analysis and modeling of sensory data, and the incorporation of chemometric data when available.
Course Materials
Books: Recommended: Sensory Evaluation of Food, Principles and Practices, 2nd edition, Harry T. Lawless and Hildegarde Heyman, Springer, 2010; Other course materials will be provided as required
Other Materials: [NA]
Fees: TBD
|
Course Learning Outcomes (students will be able to:) |
Activities Supporting the Learning Outcomes | Assessment of the Learning Outcomes |
|---|---|---|
| Utilize statistical software to analyze sensory data sets | Analysis of data sets using a variety of uni- and multivariate techniques; preparation of semester project | biweekly homework assignments, semester project/take home final exam |
| Interpret and discuss results of statistical analysis in the context of answering a research question] | Interpretation of analyses of data sets in class; preparation of semester project | homework assignments, class discussions, semester project/take home exam |
| Evaluate the scientific literature for the adequacy of experimental design and appropriate use of statistical methods |
In class discussion of scientific literature examples, preparation of semester project/take home exam |
in class discussions, semester project/take home exam |
| Dates | Lesson Topic | Assignment | Assessment |
|---|---|---|---|
|
Week 1 |
Course overview, intro to R and other statistical software | ||
| Week 2 |
Data evaluation | Working with data | Homework #1 |
| Week 3 |
Experimental Design | ||
| Week 4 |
ANOVA and MANOVA | ANOVA examples | Homework #2 |
| Week 5 |
Power Analysis, Error | Semester project 1st draft; approval of data sets | |
| Week 6 |
Principal Component Analysis | Power analysis examples, PCA | Homework #3 |
| Week 7 |
Correspondence Analysis | ||
| Week 8 |
Multidimensional Scaling, Napping, | Correspondence and scaling examples, napping | Homework #4 |
| Week 9 |
Multi-Factor Analysis (MFA) | ||
| Week 10 |
Generalized Procrustes Analysis (GPA) | MFA and GPA examples | Homework #5 |
| Week 11 |
Cluster analysis, heat mapping | 2nd draft of semester project | |
| Week 12 |
Discriminant analysis (CVA/LDA) | Cluster analysis and mapping examples | Homework #6 |
| Week 13 [dates] |
PLS modeling | ||
| Week 14 [dates] |
Preference mapping | PLS modeling examples | Homework #7 |
| Week 15 [dates] |
Consumer segmentation |
Expectations for Student Effort
For each hour of lecture equivalent, students should expect to have two to three hours of work outside of class, including readings, homework assignments and the semester project.
Grading
| Type of Assignment (tests, papers, etc) | Points | Percent of Overall Grade |
|---|---|---|
| Homework assignments | 50 each | 46.7 |
| semester project drafts | 100 each | 26.7 |
| final project/take home exam | 200 | 26.6 |
| Grade | Percent | Grade | Percent |
|---|---|---|---|
| A |
>93.0 |
C | 73.0-76.9 |
| A- | 90.0-92.9 | C- | 70.0-72.9 |
| B+ | 87.0-89.9 | D+ | 67.0-69.9 |
| B | 83.0-86.9 | D | 63.0-66.9 |
| B- | 80.0-82.9 | F | <63.0 |
| C+ | 77.0-79.9 |
Grades will be rounded up if the student's score falls between grade levels
Attendance and Make-Up Policy
This course meets over three times weekly. Students are expected to attend all scheduled lectures or sessions. If absent for a lecture or session, the student is solely responsible for course content that was missed.
Academic Integrity Statement
You are responsible for reading WSU's Academic Integrity Policy, which is based on Washington State law. If you cheat in your work in this class you will:
-be referred to the Office of Student Conduct and may fail the assignment or the course.
-Be reported to the Center for Community Standards
-Have the right to appeal my decision
-Not be able to drop the course of withdraw from the course until the appeals process is finished
If you have any questions about what you can and cannot do in this course, ask me.
If you want to ask for a change in my decision about academic integrity, use the form at the Center for Community Standards website. You must submit this request within 21 calendar days of the decision.