From 7179d84c39dfd6b4a880b39bce223600210150fa Mon Sep 17 00:00:00 2001 From: Degoot-AM Date: Mon, 24 Jun 2024 17:48:20 +0100 Subject: [PATCH] correcting typos --- episodes/describe-cases.Rmd | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/episodes/describe-cases.Rmd b/episodes/describe-cases.Rmd index 10ebe134..bac21804 100644 --- a/episodes/describe-cases.Rmd +++ b/episodes/describe-cases.Rmd @@ -255,9 +255,10 @@ confidence interval and using 100 bootstrap samples. ## Visulaziantion with ggplot2 -`{incidence2} produces basic plots for epicurves, but additional work is required to create well-annotated graphs. However, using the {ggplot2} package, you can generate more sophisticated and better-annotated epicurves. -{ggplot2} is a comprehensive package with many functionalities, but we will focus on three key elements essential for producing epicurves: histogram plots, scaling date axes and their labels, and general plot theme annotation. -The example below demonstrates how to configure these three elements for a simple `{incidence2} object. + +`{incidence2}` produces basic plots for epicurves, but additional work is required to create well-annotated graphs. However, using the `{ggplot2}` package, you can generate more sophisticated and better-annotated epicurves. +`{ggplot2}` is a comprehensive package with many functionalities, but we will focus on three key elements essential for producing epicurves: histogram plots, scaling date axes and their labels, and general plot theme annotation. +The example below demonstrates how to configure these three elements for a simple `{incidence2}` object. ```{r, message=FALSE, warning=FALSE} breaks <- seq.Date(