From f4970d7a09d958bfe5a93b4efadd5854fd155a32 Mon Sep 17 00:00:00 2001
From: Iakov Davydov <671660+idavydov@users.noreply.github.com>
Date: Wed, 16 Oct 2024 12:15:36 +0200
Subject: [PATCH] code review by Juliane

Co-authored-by: julianesiebourg <51031392+julianesiebourg@users.noreply.github.com>
---
 vignettes/basic_examples.Rmd | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/vignettes/basic_examples.Rmd b/vignettes/basic_examples.Rmd
index 70576e9b..f0745a5e 100644
--- a/vignettes/basic_examples.Rmd
+++ b/vignettes/basic_examples.Rmd
@@ -14,7 +14,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-This vignette demonstrates the use of the `deisngit` package with a series 
+This vignette demonstrates the use of the `desingit` package with a series 
 of examples deriving from the same task, namely to randomize samples of a 
 two-factor experiment into plate layouts. We shall start with the most basic
 use and gradually exploring some basic yet useful utilities provided
@@ -76,7 +76,7 @@ samples <- bind_rows(replicate(n_reps, animals, simplify = FALSE),
 
 samples |>
   head(10) |>
-  arrange(animal, group, replicate) %>%
+  arrange(animal, group, replicate) |>
   gt::gt()
 ```
 
@@ -287,7 +287,7 @@ and to plot the plate layout. If necessary, you can retrieve the samples from
 the BatchContainer instance `bc` with the method `bc$get_samples()`, or move
 samples with the method `bc$move_samples()`. The better approach usually is to 
 optimize the design with `optimize_design()`.
-3. The scoring function can be set by passinrg `scoring` parameter to the
+3. The scoring function can be set by passing `scoring` parameter to the
 `optimize_design()` function. The sample assignent is optimized by shuffling
 the samples.
 4. Various options are available to further customize the design.