Department of Mathematical Sciences


“The best thing about being a statistician is that you get to play in everyone else's backyard” —John Tukey (Bell Labs and Princeton University)

What is statistics?

Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty; and it thereby provides the navigation essential for controlling the course of scientific and societal advances (Davidian & Louis 2012).

What do statisticians do?

Statisticians apply statistical thinking and methods to a wide variety of scientific, social, and business endeavors in such areas as astronomy, biology, education, economics, engineering, genetics, marketing, medicine, psychology, public health, sports, among many.

Areas of Research


Besides population dynamics this research also covers topics as

  • evolutionary biology
  • population genetics
  • ecology
  • conservation biology
  • functional genomics


An important activity is statistical modelling and analysis of data from genomics, where multiple hypothesis testing is a central research topic. Ongoing research also includes exact hypothesis testing concerning parameters of discrete distributions in the presence of nuisance parameters.

Industrial Statistics

The main research topics include

  • Design of Experiments (DOE)
  • reliability analysis
  • extreme value statistics

In reliability, focus is modelling and statistical inference in connection with repairable and maintainable systems and calculation of system reliability of structural systems.

In extreme value statistics, focus is estimation of extreme responses of dynamic structures and extreme value prediction from sampled time series.

The research in Design of Experiments (DOE) is directed towards projection properties of non-regular two-level designs.

Stochastic Spatial and Spatio-temporal Modelling

Focus is on stochastic modelling of spatial and spatio-temporal phenomena and inference of the associated model parameters. Based on indirect observations of the phenomena Bayesian inversion with prior models of the type mentioned above is performed. Various types of Gaussian random fields and Markov random fields are mostly used.

Moreover, simulation algorithms, approximations and decision analysis for complicated spatial and spatio-temporal models are being studied. The research is inspired by challenges in characterization of petroleum reservoirs.

Computations Statistics

Research is directed towards speeding up algorithms for handling complex statistical problems. Special focus is given to Gaussian Markov random fields and applications of the approach INLA which makes it possible to avoid MCMC for doing Bayesian inference for latent Gaussian models.

Theoretical Statistics

Topics studied are characteristic functions and choice of smoothing parameters in kernel density estimation and methods for Monte Carlo computation of conditional distributions given sufficient statistics.


Bo Henry Lindqvist Professor Bo Henry Lindqvist, Head of the Statistics group


Staff – Statistics group

Strategic Research Areas



Building practical computational efficient non-stationary spatio-temporal models

In this Norwegian Research Council supported project, we will develop computational efficient models for spatio-temporal models with optional non-stationarity. The models will be available in the R-INLA package.

Penalized Complexity-priors: A new tool to define default priors and robustify Bayesian models

The main objective in this Norwegian Research Council supported project is to develop a new framework for specifying a class of default priors at model level. This will not only facilitate the ways priors are determined in practice but also robustify Bayesian analyses. The results will be made available in the R-INLA package.

Uncertainty in Reservoir Evaluation

The URE project is supported by the Norwegian Research Council and a number of petroleum companies. The vision is to provide creative, mathematically based solutions to recognized challenges in reservoir evaluation, and to develop methodologies for analysis of spatial and spatio-temporal phenomena.

Prediction of gas and oil. 3D figure.


Research centres with participating statisticians from IMF:

Centre for Biodiversity Dynamics (CBD)

Interdisciplinary centre at NTNU for research into changes in time and space of biological diversity at different organismal levels. Main research areas:

  • population dynamics
  • evolutionary biology
  • community dynamics

Centre for Ships and Ocean Structures (CeSOS)

Focus is on development of fundamental knowledge concerning the design and operation of future ships and ocean structures by integrating theoretical and experimental research in marine hydrodynamics, structural mechanics and automatic control.

Statistics at NTNU

The statistics group at the Department of Mathematical Sciences consists of

  • 17 permanent faculty members
  • 1 postdoc
  • 1 full-time researcher
  • 15 PhD-students

NTNU is the leading university in Norway in terms of number of Master degrees awarded. The group's research includes computational statistics, extreme value theory, design of experiments, reliability analysis, spatial statistics, theoretical statistics, functional genomics, and stochastic and statistical modeling in ecology, evolution and conservation biology.