diff --git a/Topic_Model_Script.R b/Topic_Model_Script.R
index 085fa00..5824f51 100644
--- a/Topic_Model_Script.R
+++ b/Topic_Model_Script.R
@@ -1,6 +1,6 @@
-We're going to use a library called 'tm', and another called 'topic models'
-#install.package("tm")
-#install.package("topicmodels")
+#We're going to use a library called 'tm', and another called 'topic models'
+#install.packages("tm")
+#install.packages("topicmodels")
 library(tm)
 
 #### instead of using 'setwd()' function, start by finding the file in the bottom right quadrant of R Studio
@@ -42,10 +42,10 @@ nrow(a.tdm) #number of unique words in corpus
 findAssocs(a.tdm, 'includ', 0.25) # find associated words and strength of the common words.play around with this
 a.tdm.sp <- removeSparseTerms(a.tdm, sparse=0.987) #remove sparse terms, maybe not necessary, sometimes is. Play around with this if you're not getting good output.
 a.tdm.sp.df <- as.data.frame(inspect(a.tdm.sp)) # convert term document matrix to data frame
-nrow(a.dtm.sp.df) # check to see how many words we're left
+nrow(a.tdm.sp.df) # check to see how many words we're left
 
 require(slam)
-a.dtm.sp. <- t(a.tdm.sp) # transpose term document matrix into document term matrix
+a.dtm.sp.t <- t(a.tdm.sp) # transpose term document matrix into document term matrix
 
 
 require(topicmodels)