آموزش r برای دانشجویان روانشناسی
نمونه گیری تصادفی در R
Generate a set of Sample data from a Data set in R Programming – sample() Function
sample() function in R Language creates random sample based on the parameters provided in the function call. It takes either a vector or a positive integer as the object in the function parameter.
Syntax:
sample(data, size, replace = FALSE, prob = NULL)
Parameters:
data can be a vector or a dataframe
size represents the size of the sample
replace is used to set the values again repeated if it is set to true
prob: a vector of probability weights for obtaining the elements of the vector being sampled
Example 1: Generate sample data from the vector
# consider the vector
data=c(23,45,21,34,5,6,7,8,86,45,3)
# get 4 random elements
print(sample(data,4))
# get 1 random element
print(sample(data,1))
# get 6 random elements
print(sample(data,6))
Output:
[1] 45 7 5 34
[1] 3
[1] 5 23 8 21 6 45
Example 2:
# Create sample
x <- sample(1:100, 10, replace=TRUE)
# Print
# Output may differ each time the command is executed
print(x)
#output
[1] 47 52 22 98 75 94 91 94 42 53
Example 3: Random Sampling of Data Frame Rows Using sample Function
# create dataframe with 2 columns
data=data.frame(col1=c(1:10),col2=c(12:21))
# get the sample of 4 in each column
data[sample(1:nrow(data), size = 4), ]
#output
Example 4:Random Sampling of Data Frame Rows Using sample Function
#از داده های mtcars میخواهیم استفاده کنیم
# Create sample
pos <- sample(1:nrow(mtcars), 5, replace = TRUE)
# Print sample observations
# Output may differ each time the command is executed
print(mtcars[pos, ])
#or
mtcars[sample(1:nrow(mtcars), 5, replace = TRUE),]
#output
mpg cyl disp hp drat wt qsec vs am gear carb
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet 4 Drive.1 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Example 5:
> df = data.frame(matrix(rnorm(20), nrow=10))
> df[sample(nrow(df), 3), ]
X1 X2
9 -0.3983045 0.7157506
2 -1.1334614 -0.1973846
10 -0.9060305 2.3234110