diff --git a/README.md b/README.md
index dbc8cc521..351f0081d 100644
--- a/README.md
+++ b/README.md
@@ -213,7 +213,7 @@ evaluation(materiality = NULL, min.precision = NULL, method = 'poisson',
 - `stringer.lta`: Stringer bound with LTA correction (Leslie, Teitlebaum, & Anderson, 1979).
 - `stringer.pvz`: Modified Stringer bound (Pap & van Zuijlen, 1996).
 - `rohrbach`: Rohrbach's augmented variance estimator (Rohrbach, 1993).
-- `moment`: Modified moment bound (Dworing & Grimlund, 1984).
+- `moment`: Modified moment bound (Dworin & Grimlund, 1984).
 - `coxsnell`: Cox and Snell bound (Cox & Snell, 1979).
 - `mpu`: Mean-per-unit estimator (Touw & Hoogduin, 2011).
 - `direct`: Direct estimator (Touw & Hoogduin, 2011).
diff --git a/man/auditPrior.Rd b/man/auditPrior.Rd
index cae6c85c4..639d51a25 100644
--- a/man/auditPrior.Rd
+++ b/man/auditPrior.Rd
@@ -64,8 +64,8 @@ For more details on how to use this function, see the package vignette:
 \details{
 To perform Bayesian audit sampling you must assign a prior probability distribution to the parameter in the model, i.e., the population misstatement \eqn{\theta}.
          The prior distribution can incorporate pre-existing audit information about \eqn{\theta} before seeing a sample, which consequently allows for a more efficient or more accurate estimate of \eqn{\theta}.
-         However, the default priors used in \code{jfa} are purposely indifferent towards the individual values of \eqn{\theta}. For these priors, the posterior distribution is based solely on the data from the sample, i.e., the likeihood.
-         Note that the default prior is a conservative choice of prior since it assumes all possible misstatement is equally likely before seeing information from a data sample.
+         However, the default priors used in \code{jfa} are purposely indifferent towards the individual values of \eqn{\theta} in order to 'let the data speak for themselves'.
+         Note that these default priors are a conservative choice of prior since they assume all possible misstatement to be (roughly) equally likely before seeing a data sample.
          It is therefore strongly recommended to construct an informed prior distribution based on pre-existing audit information if possible.
 
 This section elaborates on the available options for the \code{method} argument.
diff --git a/man/planning.Rd b/man/planning.Rd
index 1337ce372..bd341ed85 100644
--- a/man/planning.Rd
+++ b/man/planning.Rd
@@ -73,9 +73,9 @@ planning(
   prior = TRUE
 )
 
-# Bayesian planning using an impartial beta prior distribution
+# Bayesian planning using an impartial gamma prior distribution
 planning(
-  materiality = 0.05, expected = 0, likelihood = "binomial",
+  materiality = 0.05, expected = 0, likelihood = "poisson",
   prior = auditPrior(method = "impartial", materiality = 0.05)
 )
 }