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+##Final R assignment in Intro to Statistics course, fall semster.
+#+Written by Matan Horovitz (207130253) and Guy Amzaleg ()
+#+We have chosen a dataset of the first 600,000 commits to the  Linux Kernel Git repository - as published on Kaggle:
+#+https://www.kaggle.com/datasets/philschmidt/linux-kernel-git-revision-history
+#+This dataset examines commits made to the Linux kernel project over the last 12 years.
+raw_kernel_commits <- read.csv("/home/shmick/linux_kernel_git_revlog.csv")
+##BONUS: convert from EPOCH: as.Date(as.POSIXct(1100171890,origin = "1970-01-01"))
+View(raw_kernel_commits)
+##For question 1, we have chosen to examine whether the amount of changes (additions and deletions) vary over time.
+##A larger amount of changes per commit is correlated with a decrease in the quality of the code - as more changes
+#+are harder to track and audit, while a smaller amount of changes per commit implies stricter coding standards
+#+over time.
+##To examine the correlation, we made a subset of the dataset, discarding data which is irrelevant to our question,
+#+and summed all changes from the same commits into an aggregate - as we are not concerned about the files changed,
+#+only the total amount of changes on each individual commit.
+
+kernel_commits <- subset(raw_kernel_commits, select= c(author_timestamp,n_additions,n_deletions))
+#  Make a subset  ^ of the dataset which includes  ^ the EPOCH time,^ additions ^ and deletions. 
+#Rename the resulting dataset into friendlier column names
+colnames(kernel_commits) <- c("EPOCH","Additions","Deletions")
+#Sum additions and deletion into a new column, named "Total changes"
+kernel_commits["Total changes"] <- kernel_commits["Additions"]+kernel_commits["Deletions"]
+View(kernel_commits) #< examine the resulting dataset
+#Unite all commits with same EPOCH to get changes PER COMMIT
+kernel_commits_sum <- aggregate(. ~ EPOCH,data=kernel_commits,FUN=sum)
+                          
+View(kernel_commits_sum)
+#Measure the correlation between EPOCH time (from oldest to newest) and the total number of changes per commit.
+cor(kernel_commits_sum["EPOCH"],kernel_commits_sum["Total changes"])
+
+##QUESTION 2: measure number of columns in our dataset and calculate a permutation and combination of 
+#+that number, minus two, and 3.
+
+#Calculate total number of columns in our dataset
+n <- ncol(kernel_commits)
+View(n)
+
+##QUESTION 3: pick two categorial variables - month (?), is documentation
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