Update episodes/01-rstudio-intro.Rmd

Co-authored-by: Zhian N. Kamvar <zkamvar@gmail.com>

episodes/01-rstudio-intro.Rmd

@@ -45,7 +45,7 @@ Welcome to the R portion of the Software Carpentry workshop!
 Science is a multi-step process: once you've designed an experiment and collected
 data, the real fun begins with analysis! Throughout this lesson, we're going to teach you some of the fundamentals of the R language as well as some best practices for organizing code for scientific projects that will make your life easier.
 
-Although we could use a spreadsheet in Microsoft Excel or Google sheets to analyze our data, these tools are limited in their flexibility and accessibility. Critically, they also are difficult to share steps which explore and change the raw data, which is key to ["reproducible" research] (https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285). 
+Although we could use a spreadsheet in Microsoft Excel or Google sheets to analyze our data, these tools are limited in their flexibility and accessibility. Critically, they also are difficult to share steps which explore and change the raw data, which is key to ["reproducible" research](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285). 
 
 Therefore, this lesson will teach you how to begin exploring your data using R and RStudio. The R program is available for Windows, Mac, and Linux operating systems, and is a freely-available where you downloaded it above. To run R, all you need is the R program.