Statistical modelling is about understanding contexts and making forecasts where coincidences and uncertainty are involved.
With the use of statistical modelling, underlying knowledge about a process is connected with data, in an objective way. The statistical models can contain a number of unknown parameters and are thus flexible. The parameters are quantified from data using different techniques. Decisions are thus based on facts and the best possible balance between the probabilities of different outcomes.
The terms statistical modelling and machine learning are often used interchangeably, but machine learning finds patterns in data to a greater extent without the use of models. NR’s biggest strength lies in our extensive experience and comprehensive knowledge of the entire toolbox. We customise and find the right method for each problem. This gives the most precise and realistic forecasts and causal relationships, including an understanding of the uncertainty in answers when it is important.