Once you successfully execute a DOE experiment, it’s time to analyze your data. This section of the documentation covers how to manage and analyze the data you collected during a DOE experiment, including how to manage any analyses you generate.
This section shows you how data can be added to Synthace executions for downstream preparation and analysis, which can be applied to other types of experiments, not just DOE.
Aligning experimental metadata with your measurements—especially when working across multiple plates—can be both tedious and error-prone. Synthace’s Prepare Data app takes the hard work out of this, so you can spend more time interpreting results, not wrangling spreadsheets. This section walks you through the key data processing steps of the tool.
With your prepared data in hand, you are ready to analyze your DOE responses. This section covers how to assess the data you collected, how to use it to build and validate models, and importantly, how to then use these models to make predictions that can inform the next steps in your experimental campaign or simply draw conclusions from your experiment.
In addition, this section introduces the key concepts, tools, and techniques you will encounter in Synthace and guides you through the process of applying them to your data using Synthace. You will also find reference material that describes the specific way the various tools are implemented in Synthace that can be used when writing up methods or attempting to reproduce results.
There’s no such thing as mistakes in Synthace - in fact, trial and error and exploration are encouraged. This section describes the features available in Synthace for keeping track of the various analysis iterations and variations that you have tried. The most important part is how Synthace allows you to save ‘frozen’ versions of your analyses as specific versions for later reference, ensuring that you don’t accidentally lose the specific analyses you drew conclusions from.