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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: 1. Ph.D. student Hans Ole Ørka 2. Ph.D. student Vegard Lien 3. Ph.D. student Nadja Thieme 4. Ph.D. student Marius Hauglin 5. Ph.D. student Liviu Ene 6. Associate Professor Terje Gobakken .
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