# R program to illustrate # stratified random sampling in geometrical distribution # Set seed for reproducibility set.seed(1) ## Creating a data frame for the following data data1<- data.frame(Level = rep(c("freshers","juniors","midlevel","seniors"),each =10), Score=rexp(40,rate=5)) ## printing data data1 ## using dplyr package to perform stratified sampling library(dplyr) stratified<-data1%>% group_by(Level) %>% sample_n(size=10) ## displaying data by score table(stratified$Score) ## displaying data by Levels table(stratified$Level) ## displaying the data in the form of matrix x<-matrix(stratified$Score,10,4) ## calculating column mean colMeans(x) colSums(x) z=colMeans(x) # sample variance for each column mean((x[,1]-z[1])^2) mean((x[,2]-z[2])^2) mean((x[,3]-z[3])^2) mean((x[,4]-z[4])^2) #combined sample mean y<-mean(x) a<-10*y #sample size * mean of sample data b<-a/40 mean(b) ### ##
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R is very popular for data analytics which was created by Ross Ihaka and Robert Gentleman in 1993. Many big companies like Google, Facebook, Airbnb etc uses this language for data analytics. R is good for software developers, statisticians and data miners.
Data type | Description | Usage |
---|---|---|
Numeric | To represent decimal values | x=1.84 |
Integer | To represent integer values, L tells to store the value as integer | x=10L |
Complex | To represent complex values | x = 10+2i |
Logical | To represent boolean values, true or false | x = TRUE |
Character | To represent string values | x <- "One compiler" |
raw | Holds raw bytes |
Variables can be assigned using any of the leftward, rightward or equal to operator. You can print the variables using either print or cat functions.
var-name = value
var-name <- value
value -> var-name
If, If-else, Nested-Ifs are used when you want to perform a certain set of operations based on conditional expressions.
if(conditional-expression){
#code
}
if(conditional-expression){
#code if condition is true
} else {
#code if condition is false
}
if(condition-expression1) {
#code if above condition is true
} elseif(condition-expression2){
#code if above condition is true
}
elseif(condition-expression3) {
#code if above condition is true
}
...
else {
#code if all the conditions are false
}
Switch is used to execute one set of statement from multiple conditions.
switch(expression, case-1, case-2, case-3....)
For loop is used to iterate a set of statements based on a condition.
for (value in vector) {
# code
}
While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.
while(condition) {
# code
}
Repeat is used tyo iterate a set of statements with out any condition. You can write a user-defined condition to exit from the loop using IF
.
repeat {
#code
if(condition-expression) {
break
}
}
Function is a sub-routine which contains set of statements. Usually functions are written when multiple calls are required to same set of statements which increases re-usuability and modularity.
func-name <- function(parameter_1, parameter_2, ...) {
#code for function body
}
function_name (parameters)
Vector is a basic data strucre where sequence of data values share same data type.
For example, the below statement assigns 1 to 10 values to x.
You can also use se() function to create vectors.
x <- 1:10
#using seq() function
x <- seq(1, 10, by=2)
the above statement prints the output as [1] 1 3 5 7 9
.