Structuring and analysing data
Easily structure and analyse your DOE data
63 articles
Prepare your data for analysis - simple transformations
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.
Prepare data - linear regression and curve fitting
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
- Improved data reshaping and calculation updatesLearn about some recent changes we have made to data reshaping and transformation calculation
- Understanding data reshaping for processing and analysisUnderstand what reshaping data is, how it works and how to use it
- Performing non-linear curve fits using 4 & 5-parameter logistic regressionLearn how to apply 4 and 5 parameter logistic fits to your data in Synthace
- Fitting bespoke curves to your dataBuild custom curve fits (Hill, Michaelis–Menten, and more) directly in Prepare Data
- Technical Documentation for Logistic Curve FitsDetails of how fits to 4 and 5 parameter logistic fits are implemented; 4PL fits 5PL fits
- Technical Documentation: Generic Curve FittingThis article provides details of how curve fitting for generic nonlinear functions is implemented for reference purposes.
- 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