diff --git a/DESCRIPTION b/DESCRIPTION
index 8680eb7c..139e18e2 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -18,7 +18,7 @@ Authors@R: c(person("Jonah", "Gabry", role = c("aut", "cre"),
 Maintainer: Jonah Gabry <jsg2201@columbia.edu>
 Description: A graphical user interface for interactive Markov chain Monte
     Carlo (MCMC) diagnostics and plots and tables helpful for analyzing a
-    posterior sample. The interface is powered by the Shiny web
+    posterior sample. The interface is powered by the 'Shiny' web
     application framework from 'RStudio' and works with the output of MCMC 
     programs written in any programming language (and has extended 
     functionality for 'Stan' models fit using the 'rstan' and 'rstanarm' 
diff --git a/R/shinystan-package.R b/R/shinystan-package.R
index 5c5c20b8..7c25b224 100644
--- a/R/shinystan-package.R
+++ b/R/shinystan-package.R
@@ -22,20 +22,20 @@
 #'   \emph{Stan Development Team}
 #' }
 #'
-#' Applied Bayesian data analysis is primarily implemented through the Markov
-#' chain Monte Carlo (MCMC) algorithms offered by various software packages.
-#' When analyzing a posterior sample obtained by one of these algorithms the
+#' Applied Bayesian data analysis is primarily implemented through the Markov 
+#' chain Monte Carlo (MCMC) algorithms offered by various software packages. 
+#' When analyzing a posterior sample obtained by one of these algorithms the 
 #' first step is to check for signs that the chains have converged to the target
-#' distribution and and also for signs that the algorithm might require tuning
-#' or might be ill-suited for the given model. There may also be theoretical
-#' problems or practical inefficiencies with the specification of the model.
-#' 'ShinyStan' provides interactive plots and tables helpful for analyzing a
+#' distribution and and also for signs that the algorithm might require tuning 
+#' or might be ill-suited for the given model. There may also be theoretical 
+#' problems or practical inefficiencies with the specification of the model. The
+#' 'ShinyStan' app provides interactive plots and tables helpful for analyzing a
 #' posterior sample, with particular attention to identifying potential problems
 #' with the performance of the MCMC algorithm or the specification of the model.
-#' 'ShinyStan' is powered by Shiny web application framework by 'RStudio' and works
-#' with the output of MCMC programs written in any programming language (and has
-#' extended functionality for models fit using the \pkg{rstan} package and the
-#' No-U-Turn sampler).
+#' 'ShinyStan' is powered by the 'Shiny' web application framework by 'RStudio' 
+#' and works with the output of MCMC programs written in any programming 
+#' language (and has extended functionality for models fit using the \pkg{rstan}
+#' package and the No-U-Turn sampler).
 #'
 #' @section 'ShinyStan' has extended functionality for 'Stan' models:
 #'
diff --git a/man/shinystan-package.Rd b/man/shinystan-package.Rd
index d398218e..43681e1d 100644
--- a/man/shinystan-package.Rd
+++ b/man/shinystan-package.Rd
@@ -10,20 +10,20 @@
   \emph{Stan Development Team}
 }
 
-Applied Bayesian data analysis is primarily implemented through the Markov
-chain Monte Carlo (MCMC) algorithms offered by various software packages.
-When analyzing a posterior sample obtained by one of these algorithms the
+Applied Bayesian data analysis is primarily implemented through the Markov 
+chain Monte Carlo (MCMC) algorithms offered by various software packages. 
+When analyzing a posterior sample obtained by one of these algorithms the 
 first step is to check for signs that the chains have converged to the target
-distribution and and also for signs that the algorithm might require tuning
-or might be ill-suited for the given model. There may also be theoretical
-problems or practical inefficiencies with the specification of the model.
-'ShinyStan' provides interactive plots and tables helpful for analyzing a
+distribution and and also for signs that the algorithm might require tuning 
+or might be ill-suited for the given model. There may also be theoretical 
+problems or practical inefficiencies with the specification of the model. The
+'ShinyStan' app provides interactive plots and tables helpful for analyzing a
 posterior sample, with particular attention to identifying potential problems
 with the performance of the MCMC algorithm or the specification of the model.
-'ShinyStan' is powered by Shiny web application framework by 'RStudio' and works
-with the output of MCMC programs written in any programming language (and has
-extended functionality for models fit using the \pkg{rstan} package and the
-No-U-Turn sampler).
+'ShinyStan' is powered by the 'Shiny' web application framework by 'RStudio' 
+and works with the output of MCMC programs written in any programming 
+language (and has extended functionality for models fit using the \pkg{rstan}
+package and the No-U-Turn sampler).
 }
 \section{'ShinyStan' has extended functionality for 'Stan' models}{