Overview
The simple linear fit transformation in Synthace enables you to derive key parameters like slope and intercept from your raw data. These values can be used directly as responses in your analysis or combined with other transformations. This guide walks you through how to use this feature effectively.
Step-by-step instructions
Reshape Your Data
Before fitting, your data should be in a wide format, with each timepoint in a separate column.
Go to the reshape tab.
Select a time variable (e.g.,
t) as the pivot axis.The resulting table will show one row per experimental run and one column per time point.
Apply the linear fit transformation
Navigate to the calculate tab.
Choose linear fit from the list of transformations.
Select:
Independent variable (typically time)
Dependent variable(s) (measurement columns)
Provide a unique column name for your new response. Synthace will create a placeholder name for you using the names of your x and y variables.
You can optionally force the fitted line to go through the origin (x=0, y=0) — useful when a zero signal is expected at time zero.
Understanding the output columns
This transform adds seven new columns for each fitted line:
Column | Description |
Slope | Rate of change (y per unit x) |
Slope Standard Error | Estimate of uncertainty in the slope |
Intercept | Y value when X = 0 |
Intercept Standard Error | Estimate of uncertainty in the intercept |
p-value | Test of whether the slope is significantly different from 0 |
R² | Goodness of fit (0–1) |
Fit Error | Flags issues with the fitting process (e.g., missing data) |
These derived values are now available for further transformations or downstream modeling.
Review fit quality
Synthace automatically highlights the 3 best and 3 worst fits based on R². You can:
Preview individual fits by selecting rows in the table.
View fitting errors or anomalies directly.
This helps you quickly assess whether your dataset is suitable for linear modeling.
Note: A maximum of 8 lines of fit can be displayed simultaneously. Lines will be automatically removed if you try to select > 8.
Analyze derived responses
Once applied:
Derived responses appear as new columns in your dataset.
You can use these new derived responses to run full response analyses.
Identify significant DOE factors influencing slope, intercept, or R².
Download your dataset, complete with your new response, for offline analysis or record keeping.