02930 The Analysis of Sensory and Consumer Data

2016/2017

Kurset udbydes kun i ulige år.
Kursusinformation
The Analysis of Sensory and Consumer Data
Engelsk
2,5
Ph.d., Servicekursus (faglige færdigheder)
Kurset udbydes under tompladsordningen
August
Planlægges afholdt 28 August - 1 September 2017.
Campus Lyngby
The course will be offered jointly in two ways: 1) A regular course with participants present at the Lyngby campus and 2) A web based course with only virtual presence during the week.
Forelæsninger og computerøvelser
[Kurset følger ikke DTUs normale skemastruktur]
Bedømmelse af øvelser
Active participation in exercise work together with participant presentations and/or submissions of exercise results form the basis for completing and passing the course.
bestået/ikke bestået , intern bedømmelse
The course is aimed at Ph.D-students within non-statistical areas such as sensory science, food science, marketing etc. with interest in data analysis and statistics. It is also well suited for sensory practitioners from industry and scientific institutions or for Ph.D. students within Statistics/Data analysis with interest in human perception data.
Minimum 15
Per B. Brockhoff , Lyngby Campus, Bygning 324, Tlf. (+45) 4525 3365 , perbb@dtu.dk

01 Institut for Matematik og Computer Science
http://www2.compute.dtu.dk/courses/02930/
I studieplanlæggeren
22. Juli 2017
Non DTU students: check website http:/​/​www2.compute.dtu.dk/​courses/​02930/​
Overordnede kursusmål
At forbedre evnen til at analysere human perception data. Nogle af de nyeste statistiske metoder bliver gennenmgået ved brug af open source softwaren R, ved brug af bla. R-pakkerne sensR, ordinal, SensMixed og lmerTest samt programmerne PanelCheck og ConsumerCheck.
Læringsmål
En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:
  • Arbejde med R, Panelcheck og ConsumerCheck
  • Planlægge og analysere simple diskrimination og similaritets experimenter ved brug af sensR
  • Analysere replikerede diskriminationsdata
  • Udføre og forstå simpel Thurstonian modelling
  • Anvende mixed models på sensorisk profildata og forbrugerpræference data ved hjælp af PanelCheck og ComsumerCheck
  • Analysere sensorisk profildata med den nyeste skaleringskorretionsmetode (med R)
  • Bruge PanelCheck og ConsumerCheck til simple såvel som multivariate analyser (inclusive Tucker-1)
  • Bruge R-pakkerne lmerTest og SensMixed til at analysere non-standard data med mixede modeller
  • Analysere ordinal human perception data ved hjælp af R-pakken ordinal
  • Visualisere ANOVA resultater med den nyeste delta-tilde metode ved hjælp af R shiny App'en SensMixed.
  • Kende til den nyeste sensometriforskning ved DTU Sensometrics Group
Kursusindhold
Course Main Topics Overview:

Monday: Simple discrimination using R (package sensR)
Tuesday: Basic mixed models using PanelCheck, Consumercheck and R.
Wednesday: Multivariate Analysis using PanelCheck and ConsumerCheck
Thursday: More advanced discrimination using R (packages sensR and ordinal)
Friday: More advanced mixed models (packages SensMixed and lmerTest)
Litteraturhenvisninger
Brockhoff P. B., Amorim I., Kuznetsova A., Søren Bech, Lima R. R. (2016). Delta-tilde interpretation of standard linear mixed model results, Food Quality and Preference, Vol 49, 129-139.

T. Næs, P.B. Brockhoff and O. Tomic, (2010). Statistics for Sensory and Consumer Science, John Wiley & Sons.

Brockhoff, P.B. and Christensen, R.H.B. (2010). Thurstonian models for sensory discrimination tests as generalized linear models. FQP, 21(3), 330-338.

Brockhoff, P. B., Schlich, P., & Skovgaard, I. (2015). Taking individual scaling differences into account by analyzing profile data with the Mixed Assessor Model. FQP, 39, 156-166.

Christensen, R.H.B. Cleaver, G. and Brockhoff, P.B. (2011). Statistical and Thurstonian models for the A-not A protocol with and without sureness, FQP 22(6), 542-54.

Kuznetsova, A., Christensen, R.H.B., Bavay, C. and Brockhoff, P.B. (2015). Automated mixed ANOVA modeling of sensory and consumer data. FQP 40 (2015) 31-38
Sidst opdateret
25. april, 2016