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MetaSys-LISBP · Oct 26, 2023 · e5f70c0 · e5f70c0
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diff --git a/docs/faq.rst b/docs/faq.rst
@@ -76,7 +76,7 @@ The quality of the fit can be evaluated based on:
 What is a χ² test?
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-A χ² test describes how well a model fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model used in PhysioFit (see the :doc:`models` section). It is calculated as the sum of differences between measured and simulated values, each squared and divided by the simulated value.
+A χ² test describes how well a model fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model used in PhysioFit (see the :doc:`method` section). It is calculated as the sum of differences between measured and simulated values, each squared and divided by the simulated value.
 A good fit corresponds to small differences between measured and simulated values, thereby the χ² value is low. In contrast, a bad fit corresponds to large differences between simulations and measurements, and the χ² value is high. 
 
 The resulting χ² value can then be compared with a χ² distribution to determine the goodness of fit. The p-value of one-tail χ² test is calculated by PhysioFit from the best fit and is given in the log file (have a look to the :doc:`usage` section). A p-value close to 0 means poor fitting, and a p-value close to 1 means good fitting (keeping in mind that a p-value very close to 1 can be an evidence that standard deviations might be overestimated). A 

diff --git a/docs/method.rst b/docs/method.rst
@@ -52,8 +52,8 @@ more details on the interpretation of the khi2 test results.
 Sensitivity analysis
 *********************
 
-To determine the precision on the fit and on the estimated parameters (including fluxes), PhysioFit performs a Monte Carlo analysis. Briefly, several 
-noisy datasets are generated from the simulated dynamics of the best fit (i.e defined in parameter :samp:`number of iterations` of the GUI) and calculate fluxes and other growth 
+To determine the precision on the fit and on the estimated parameters (including fluxes), PhysioFit performs a Monte Carlo analysis. Briefly, PhysioFit generates several 
+datasets by adding noise to the dynamics simulated from the best fit, and calculated fluxes and other growth 
 parameters for each of these synthetic datasets. This enables PhysioFit to compute statistics (mean, median, standard deviation and 95% confidence interval) for 
-each parameter. We recommend always running a sensitivity analysis when using PhysioFit.
+each parameter (including fluxes). We recommend always running a sensitivity analysis when using PhysioFit.