In order to create a successful brick, we needed to try out different combinations of growth medium and preparation of the bricks to gain the best compressive strength. An important factor when designing experiments is to decide what to test and which combinations are needed. Figuring this out without any help is pretty much impossible, which is why we approach it by modelling the experimental design. By doing this we can reduce the number of experiments significantly.

Two experimental designs were successfully created and carried out utilizing the optimal design approach for the compressive strength experiments. The designs were a replicated design with 17 trials, with four replicates, and an unreplicated full factorial design with 64 trials.

The data obtained in these experiments, lead to the creation of multiple statistical models. The aim of the models are to link the factors of burning time, burning temperature, substrate, incubation time, mixing ratio and density to compressive strength. The models enable us to predict the optimal processing of the fungal bricks, ensuring that the best possible compressive strength can be achieved.

To identify the best models, the following steps are carried out:

1. Explorative and a descriptive analysis of the data. This was done at first to identify if any immediate trends can be discovered, which have to be taken into account in the modelling process.
2. The actual modelling process, where different types of models are fitted and considered based on the explorative analysis.
3. Modelling selection process, where the models are compared to determine which model describes the data best, with regards to parameter choice, likelihood and so on.
4. Post hoc analysis to quantify uncertainties of the parameters, prediction uncertainty and contrast comparison.

With these four steps the optimal statistical model can be identified by linking compression strength to the previously mentioned parameters.