**DTU Ph.D.-course (02930)**

**Analysis
of Sensory and Consumer Data
**

at the

**Technical University of Denmark, **

**Lyngby, Denmark**

**The course will NOT run in 2017 and there are currently no plan for when or if the course will run again**

Organized by:

Per Bruun Brockhoff, DTU Compute

- Get support for the planning and analysis of your experiments
- Get dedicated courses
- Co-finance collaborative research projects e.g. Ph.D projects
- Get support for dedicated implementations of some of the methodology - e.g. by personalized R Shiny web applications meeting your needs
- Etc

Don't hesitate to contact us:

Per Bruun Brockhoff , Email: perbb@dtu.dk

**Course Objectives**

To
improve the ability of analysing human perception
data. Some of the newest statistical methodologies will be
covered using the open source software R. The packages sensR, ordinal, SensMixed
and lmerTest will be used together
with the free software packages PanelCheck and ConsumerCheck.

**Learning Objectives**

A
student who has met the objectives of the course will be able to:

·
Work with R,
Panelcheck and ConsumerCheck

·
Plan and analyze
simple discrimination and similarity experiments using sensR

·
Analyze replicated
discrimination data

·
Perform and
understand simple Thurstonian modeling

·
Use mixed models
for sensory profile data and consumer preference data by PanelCheck
and ConsumerCheck

·
Analyze sensory
profile data with the newest scale correction method (using R)

·
Use PanelCheck and ConsumerCheck for
simple analysis as well as multivariate analysis (including Tucker-1)

·
Use the R-packages
lmerTest and SensMixed to
analyze non-standard data with mixed models

·
Analyze ordinal
human perception data using the R-package ordinal

·
Visualize ANOVA results by the newest
delta-tilde method using the SensMixed R shiny application

·
Know about the newest sensometrics
research going on at the DTU Sensometrics group

**Participants**

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.

**Language**

All lectures and activities will be given in English.

**Organizers**

Professor Per Bruun Brockhoff, B324, R220, (+45) 2044 1711, perbb@dtu.dk

**Programme**, **overview**

·
Monday: Basic discrimination testing using R (package sensR)

·
Tuesday: Basic mixed models using PanelCheck, ConsumerCheck and R (package SensMixed).

·
Wednesday: Multivariate Analysis using PanelCheck
and ConsumerCheck

·
Thursday: More advanced discrimination testing using R (replicates etc)(packages sensR and ordinal)

· Friday: More Advanced mixed models using R-package
lmerTest (and lme4)

We begin Monday morning at 9am and finish Friday at 3pm.

**Teachers:**

Professor Per Bruun Brockhoff

DTU Compute, Technical University of Denmark

**Study Material:**

1.
Brockhoff (2011), Sensometrics. In: International Encyclopedia of Statistical Science, Lovric,
Miodrag (Ed.), Springer.

2.
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.

3.
T. Næs, P.B. Brockhoff and O. Tomic,
(2010). Statistics for Sensory and Consumer Science, John Wiley & Sons.

4.
Brockhoff, P.B. and Christensen, R.H.B. (2010). Thurstonian
models for sensory discrimination tests as generalized linear models. FQP,
21(3), 330-338.

5.
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.

6.
Christensen, R. H. B., & Brockhoff, P. B. (2013). Analysis of sensory ratings
data with cumulative link models. J. Soc. Fr. Stat. & Rev. Stat. App.,
154(3), 58-79.

7.
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.

8.
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

We will supplement with a number of guides/tutorials
and newest papers.

**Social activity**

Coffee for coffee
breaks, lunches and one dinner at a restaurant in Copenhagen is
provided for everyone.

**Housing **

You can find information on Visit Copenhagen's website.

**Laptops**

Students are required to bring their own laptops for the computer
exercises.

**R software**

We will use the software R throughout the course, and we ask all
participants to install R on their laptop in advance of the course. We also ask
that you install the graphical user interface (GUI) / Integrated development
environment (IDE) RStudio. If you are a confident R
user and acustumed to a different GUI, feel free to
use that one (though we strongly discourage the standard GUI that comes with
R). Both R and RStudio are open source and free of
charge.

To install R go to http://cran.r-project.org/
and follow the installation instructions.

To install RStudio go to http://www.rstudio.com/products/rstudio/download/
and choose according to your operating system.

For further assistance, see the following short intro (with relevant links) to
get started with R and RStudio:

*R introduction -
get started (incl. Rstudio). (New 2015 )(13 min)*

If you want to watch a few very short videos on how to get
started with

R then you can go to this Youtube Playlist:

**http://www.youtube.com/playlist?list=PLOU2XLYxmsIK9qQfztXeybpHvru-TrqAP**

(A number of short videos illustrating the use of R - shown within a Mac
version,

but apart from the appearance of the sub-windows exactly the same works for RStudio

in any operating system)

**Basic Statistics
Brush-up??**

We will assume that you have a background
with (at least) an introductory statistics class. If p-values or the idea of
confidence intervals etc is a bit far away for you, you can find topic
wise categorized links to podcasts on all topics of an introductory statistics
class here:

**http://introstat.compute.dtu.dk/podcast/modulized-and-ordered-uk-podcast-links/**

You can also
find a complete online textbook on statistics:

**http://introstat.compute.dtu.dk/enote/**

**More advanced
statistics
**In the

**Mixed models:**

At the website of DTU
course 02429:

you will find a complete online textbook on applied linear mixed models, and
also a complete collection of small podcasts taking you through the course. You
will find some introductory lectures there, that you
might spend some minutes viewing.

**Chemometrics****:**

At the website of DTU
course 27411:

you will find some podcasts on e.g. Principal Component Analysis.

**Looking very much forward to welcoming you in Wonderful Copenhagen!**