address task 15, issue carpentries-incubator/issues/112

episodes/01-introduction-to-high-dimensional-data.Rmd

@@ -55,8 +55,8 @@ pose a challenge for data analysis as standard methods of analysis, such as line
 regression, are no longer appropriate.
 
 High-dimensional datasets are common in the biological sciences. Subjects like
-genomics and medical sciences often use both tall (in terms of $n$) and wide
-(in terms of $p$) datasets that can be difficult to analyse or visualise using
+genomics and medical sciences often use both tall (large $n$) and wide
+(large $p$) datasets, which can be difficult to analyse or visualise using
 standard statistical tools. An example of high-dimensional data in biological
 sciences may include data collected from hospital patients recording symptoms,
 blood test results, behaviours, and general health, resulting in datasets with