Structuring and analysing data
Easily structure and analyse your DOE data
57 articles
Structuring and Analysing DataHow to manage and analyze the data you collected during a DOE experiment
Prepare your data for analysis
Easily perform pre-processing of your data prior to analysis and model fitting
Data structuring and preparation
Prepare DOE Data in Synthace: Reshape, Transform, and AnalyseThis documentation provides an overview of the new data preparation functionality within the Synthace platform.
Data Preparation for DOE Analysis: A Step-by-Step GuideThis guide will walk you through the improved data preparation features for Design of Experiments (DOE) analysis.
Reshape your data ready for analysisLearn how you reshape your data set ready for downstream pre-processing and analysis
Calculating Mean, Standard Deviation & Z′ Factor in SynthaceLearn how to use pre-defined data calculations, such as mean, standard deviation and z-factor
Creating custom data transformationsBuild custom calculations with your data, upload new responses and factors, and apply transformations, like Log(), to your response(s).
Saving prepared data setsThis documentation provides a concise guide to the data preparation process within the application, focusing on state saving.
Updating data preparation sessions and transformationsReview the process for editing data calculations and reshaping steps, Learn about transformation management and the editing process.
Additional tools - Data preparationLearn the process of collaborating on prepared datasets. It covers sharing datasets, editing, and saving different versions for analysis.
Response Analysis
What is linear statistical modelling?
Introduction to linear statistical modelling for DOE
Model fundamentals, and what does linear mean anyway?
Putting it together: the modelling loop
Before you start modelling, visualize your data
Why is visualizing your data a great place to start?
How to create plots of your data
How to create plate maps of your data
Identifying significant effects and fitting models
Choosing the effects to include in your model
The Find Effects Tab
What does Find Effects do?
Statistical Reference for Find Effects
How to find significant effects
How to manually adjust effects of interest
How to use significant effects plots
Fitting a stepwise regression model
What are stepwise regression models?
The statistics behind stepwise regression models
Fitting a LASSO regression model
What are LASSO regression models?
The statistics behind LASSO regression models
Assessing your model quality
Validating Your Model
The statistics behind model diagnostics
Improving your model iteratively
Fixing Model Validation Issues: Transformations and Row Sets
The statistics behind transformations
How to select and save subsets of my data
How to apply and save a predefined transform to my data
How to perform predefined column based calculations to my data
How to apply and save a custom transform to my data
Exploring your models and making predictions
What can you use your models for?
The Statistics Behind Model Prediction
How to predict the best conditions from your model
How to predict the best conditions from multiple models
How to use your model to decide on next steps
Browsing Models
Statistical Reference for Browse Models
Blocking factors
Deriving complex responses from your data
Use linear and non-linear transformations to extract deeper insights from raw data.
When and why to use simple linear model fits to derive responses in SynthaceA basic introduction to fitting simple linear models to your response data
How to use the simple linear fit transformation in SynthaceLearn how to use the Linear Fit transformation on the data preparation ap