Fix a typo

paper/paper.md

@@ -39,7 +39,7 @@ Furthermore, `uravu` provides the functionality to create simple, publication-qu
 
 Alongside API information, the `uravu` documentation offers brief tutorials covering many aspects of the package.
 This allows those unfamiliar with Bayesian modelling to get to grips with these important tools for data analysis.
-While Bayesian data modelling is possible with packages such as `emcee` [@foremanmackey_emcee_2019], `dynesty` [@speagle_dynesty_2020], and `PyMC3` [@salvatier_pymc3_2016], to the authors' knowledge `uravu` is unique in offering a simple to use interface, where it is not necessary to explicitly define functions for as the likelihood or prior probabilities (though custom priors are possible). 
+While Bayesian data modelling is possible with packages such as `emcee` [@foremanmackey_emcee_2019], `dynesty` [@speagle_dynesty_2020], and `PyMC3` [@salvatier_pymc3_2016], to the authors' knowledge `uravu` is unique in offering a simple to use interface, where it is not necessary to explicitly define functions for the likelihood or prior probabilities (though custom priors are possible). 
 `uravu` is being actively applied to scientific problems, such as data reduction at large scale scientific facilities and the modelling of diffusion in battery materials.
 
 # Statement of Need
@@ -54,4 +54,4 @@ Furthermore, the tutorials, available as documentation online, allow users to be
 
 This work is supported by the Ada Lovelace Centre – a joint initiative between the Science and Technology Facilities Council (as part of UK Research and Innovation), Diamond Light Source, and the UK Atomic Energy Authority.
 
-# References
+# References