Statistics and GIS assistance
An arrangement for help and advice with regard to statistics and GIS is now in operation,
principally for Master’s students.
How do you seek advice?
1. The users, i.e. students at INA, make direct contact with the person whom they think
can help and arrange a time for consultation. Remember to be well prepared!
2. Doctoral students and postdocs register the time used in Agresso (if you have
questions about this contact Gunnar Jensen).
Help with statistics
Research scientist Even Bergseng
Discipline: Forest economy, forest policies, forest models
Statistical expertise: Regression analysis, models with random and fixed effects,
controlled/truncated data, some time series modelling, parametric and non-parametric
effectiveness analyses
Software: Stata, Excel
Postdoc. Ole Martin Bollandsås
Discipline: Forest production, forest inventory
Statistics expertise: Regression analysis, sampling
Software: SAS, R
Associate Professor Sjur Baardsen
Discipline: Econometric analysis of markets in the forest sector
Statistical expertise: General, although somewhat “rusty”, expertise in many econometric
topics (all-rounder)
Software: Shazam, Frontier
Associate Professor Terje Gobakken
Discipline: GIS og long-term predictions
Statistical expertise: Regression analysis, ANOVA and PLS regression
Software: SAS, R
Ph.D. Student Espen Halvorsen
Discipline: Forest economy, forest management planning
Statistical expertise: OLS, GLS, hypothesis testing, autocorrelation, ANOVA, categorical
data, GLM, ANOVA
Software: (partly) Shazam, Minitab og JMP
Ph.D. Student Jan Vidar Haukeland
Discipline: Nature based tourism
Statistical expertise: Regression and factor analysis
Software: SPSS
Associate Professor Olav Høibø
Discipline: Wood technology
Statistical expertise: Planning of experiments, regression analysis (linear and non-linear),
ANOVA, random and non-random effects, categorical data, multivariate analysis
Software: R, JMP, Unscrambler, some SAS
Ph.D. Student Vegard Lien
Discipline: Evaluation using aircraft based laser
Statistical expertise: Regression analysis, spatial statistics, analysis of categorical data
(logistical models, etc.)
Software:
Ph.D. Student Eivind Meen
Discipline: Forest modelling and botanical ecology
Statistical expertise: General linear models (GLM), regression analysis, ANOVA, ordination
(PCA/DCA/CCA- in start phase)
Software: SAS, SAS insight og Canoco
Ph.D. Student Mari Sand Sivertsen
Discipline: Wood technology, wood for external use, surface treatment, moisture dynamics,
decomposition
Statistical expertise Planning of lab and field experiments, ANOVA, nonlinear regression
Software: JMP
Ph.D. Student Torunn Stangeland
Scientific discipline: Ethnobotany
Statistical expertise: Cluster, factor and regression analysis, logarithmic regression, ANOVA,
MANOVA, some SEM analyise. Statistical inference theory and stochastical modelling
Software: Minitab, Sigmaplot
Ph.D. Student Nadja Thieme
Scientific discipline: Forest valuation using laser
Statistical expertise: General linear models (GLM), regression analysis (linear, logarithmic),
multivariate analyses, geostatistics (interpolation, kriging methods, cross-validation)
Software: Matlab, R
Professor Ørjan Totland
Scientific discipline: Ecology
Statistical expertise: Eksperimental and correlative studies, ANOVA, Regression,
Multivariate statistics Software: SYSTAT, SPSS, CANOCO, LISREL
Ph.D. Student Hans Ole Ørka
Scientific discipline: Forest assessment using laser
Statistical expertise: Regression analysis, ANOVA, ANCOVA, mixed linear models (i.e.
models with fixed and random effects), multivariate methods (PCA, PCR, PLS), classification
and cluster analysis
Software: R
Associate Professor Vidar Selås
Scientific discipline: Ecology and nature management
Statistical expertise: Multiple regression analysis, especially linear, logarithmic and poisson
(also quasi-poisson). It is important that the students recognise the criteria for using the
different types.
Software: R, JMP
Visiting Professor II Svein Solberg
Scientific discipline: Forest damage
Statistical expertise: General linear models (GLM), regression analysis, ANOVA, ANCOVA,
mixed models, i.e. models with fixed and random effects, hierarchical models (nested
designs), type 1 and type 2 errors and power
Software: SAS
GIS-help
The following persons can assist students with GIS:
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6.
Ph.D. student Hans Ole Ørka
Ph.D. student Vegard Lien
Ph.D. student Nadja Thieme
Ph.D. student Marius Hauglin
Ph.D. student Liviu Ene
Associate Professor Terje Gobakken