Statistics for Data Science

Step 1: Chunking the data

We can read our project results data in, then use the R sample function to create our 2 two chunks of data (as trainingData and testData), as shown in the following R commands as follows:

# --- first load our project results data 
# --- from our CSV file into the object MyData 
 
MyData <- read.csv(file="c:/Worker/ProjectManagementProfit.csv", header=TRUE, sep=",") 
 
# --- next we are setting the ""sample seed"" 
# --- to reproduce results of random sampling 
 
set.seed(100)   
trainingRowIndex <- sample(1:nrow(MyData), 0.8*nrow(MyData))   
 
# --- create our ""chunk"" of  
# --- model training data 
 
trainingData <- MyData [trainingRowIndex,] 
 
# --- create our ""chunk of  
# --- test data   
testData <- MyData [-trainingRowIndex,]