Course - Descriptive Sensory Methods and Experimental design and data analysis - MATV4008
Descriptive Sensory Methods and Experimental design and data analysis
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About the course
Course content
This course consist of two parts; "Experimental design and data analysis" and "Descriptive sensory methods".
Experimental design and data analysis:-Uncertainty analysis,-Hypothesis testing,-Simple and Multiple linear regression,-Experimental design with two-level factorial experiments,-Analysis of variance (ANOVA),-Nonparametric methods,-IBM SPSS for statistical analysis.
Descriptive sensory methods: -Brief introduction to anatomy and physiology related to sensory science and the use of sensory analysis in research and industry. -Sensory methods (descriptive) and reporting of sensory results -Use of software for sensory analysis -Some statistics and multivariate analysis of sensory data.
Learning outcome
Experimental design and data analysis: The students will have comprehensive knowledge and skills in relevant theory, methods, current problems and fields of applications within the chosen topics. The student has knowledge of the basic statistical models and methods used in science and technology. The student can interpret results of hypothesis testing, regression analysis, experimental design, analysis of variance and nonparametric methods. The student can use software for statistical calculations and analyzes.
Descriptive sensory methods: The students will have comprehensive knowledge and skills in descriptive sensory research (K1, K2) and be able to obtain and use literature and research on sensory science (F2, F4). The students can interpret, discuss, present, and evaluate their work orally and in writing (F5) and be able to follow guidelines for writing the home exam (G2).
Learning methods and activities
Experimental design and data analysis: Lectures (24 h), exercises (8 h).
Descriptive Sensory Methods: Lectures (12 h), laboratory tests (6 h), seminars (8 h), individual study (40-15 h), group study (15 h) and oral presentation (2 h)
Compulsory assignments
- Four approved exercises in Statistics and research planning
- Participation in one group presentation in Descriptive sensory methods
- Participation in three laboratory exercises in Descriptive sensory methods
Further on evaluation
Experimental design and data analysis: 4 exercises must be approved to access the written exam. The compulsory exercises are valid for four semesters including the semester in which they are approved. If the course is retaken after this, the exercises must be completed and approved again.
Descriptive sensory methods: To be able to submit the home exam, the two work requirements (participation as an assessor in the three sensory tests and the group presentation) must be approved.
Each grade (written exam in Experimental design and data analysis, assignment/work in Descriptive sensory methods) counts 50% of the total grade in the course. Both the written exam and the home exam must be passed in order to pass the course.
If the course is not passed, the part that is not passed must be taken again to pass the course. When retaking the course when passed (improving the grade), students can choose which part to retake. A new home exam in descriptive sensory methods is only given after appointment with the responsible lecturer.
New/postponed written exam: In august
New/postponed home exam: By appointment with the lecturers
Specific conditions
Admission to a programme of study is required:
Biotechnology (MBIOT5)
Biotechnology (MSBIOTECH)
Chemical Engineering and Biotechnology (MTKJ)
Food Science, Technology and Sustainability (FTMAMAT)
Recommended previous knowledge
Knowledge in statistics corresponding to MATV2002 - Statistics and sensory methods, are recommended
Required previous knowledge
Admission to the course requires that you are enrolled as a student at NTNU, Trondheim. The course is compulsory for the master's students in Food Science, Technology and Sustainability (FTMAMAT)
Course materials
Experimental design and data analysis:
-Probability and Statistics for Engineers and Scientists (9th Edition) by Ronald E. Walpole.
Descriptive Sensory Methods:
-Lawless, H. T., & Heymann, H. (2010). Sensory evaluation of food: principles and practices (2 ed.). New York: Springer. (online Oria) - Delarue, J., Lawlor, J., Rogeaux, M., & Ares, G. (2015).
-Delarue, J., Lawlor, J. B., Rogeaux, M., & Ares, G. (2015). Rapid sensory profiling techniques and related methods : applications in new product development and consumer research: Vol. Number 274. Woodhead Publishing.
-Papers and lectures available on Blackboard
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Credit reductions
| Course code | Reduction | From |
|---|---|---|
| TBT4506 | 3.7 sp | Autumn 2020 |
| TBT4507 | 3.7 sp | Autumn 2020 |
Subject areas
- Technological subjects