diff --git a/index.qmd b/index.qmd
index 35856f5..960f022 100644
--- a/index.qmd
+++ b/index.qmd
@@ -18,7 +18,7 @@ We will have a healthy mix of keynotes from invited lecturers and hands-on sessi
 
 ### 💶 Costs
 
--   50€ course fee, including lunch + dinner
+-   150€ course fee, including lunch + dinner
 -   You have to pay for Hotel + Travel + Breakfast
 
 ### 💬 Typical questions that will be answered
@@ -34,4 +34,4 @@ We will have a healthy mix of keynotes from invited lecturers and hands-on sessi
 
 ### Abstract
 
-Development of software has become an important part of research projects in many areas of science and engineering. In this week-long summer school, we will therefore acquaint you with the most essential paradigms of software development, which support the design of efficient, user-friendly, and sustainable software. In particular, we will focus on the scientific programming language Julia. The summer school is organized around keynote presentations by invited Julia experts and many hands-on tutorials. First, a gentle introduction including packaging, testing, virtualization, interaction, and visualization will supply you with the essential skills you need to use Julia in your research. Afterwards, we build on these skills to implement computationally expensive statistical methods. In particular, we will focus on methods for regression and resampling using bootstrap and permutations. That is, methods addressing two of the most common challenges in statistics: estimation of the relationship between variables of interest and the quantification of uncertainty.
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+Development of software has become an important part of research projects in many areas of science and engineering. In this week-long summer school, we will therefore acquaint you with the most essential paradigms of software development, which support the design of efficient, user-friendly, and sustainable software. In particular, we will focus on the scientific programming language Julia. The summer school is organized around keynote presentations by invited Julia experts and many hands-on tutorials. First, a gentle introduction including packaging, testing, virtualization, interaction, and visualization will supply you with the essential skills you need to use Julia in your research. Afterwards, we build on these skills to implement computationally expensive statistical methods. In particular, we will focus on methods for regression and resampling using bootstrap and permutations. That is, methods addressing two of the most common challenges in statistics: estimation of the relationship between variables of interest and the quantification of uncertainty.