The R programming language has built-in functions that allow you to easily sample from a population. One such function is `sample()`

.

Here is an example of how you might use the `sample()`

function to select a random sample of 10 elements from a population of numbers from 1 to 100:

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population <- 1:100 sample_size <- 10 sample(population, sample_size, replace = FALSE) |

The `sample()`

function takes three arguments: the population, the sample size, and a Boolean value that specifies whether to sample with replacement (`TRUE`

) or without replacement (`FALSE`

). In this case, we are sampling without replacement, which means that once an element is chosen for the sample, it will not be chosen again.

The function will output a vector with 10 random number of the population.

Another way to do the same thing is to use the `runif()`

function to generate a random sample from a uniform distribution, like this:

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sample_size <- 10 runif(sample_size, min = 1, max = 100) |

Here `runif()`

function generates random numbers between a specific range, in this case between 1 and 100.

You can also use other probability distributions, such as normal distribution(rnorm()) or exponential distribution(rexp()) to generate samples.

Please note that these are just examples, you should check your data properties before applying these functions and also carefully choose the parameters that corresponds to your distribution.

Let me explain the code you provided:

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population <- 1:100 sample_size <- 10 sample(population, sample_size, replace = FALSE) |

`population <- 1:100`

: This line creates a vector called`population`

that contains all of the numbers from 1 to 100.`sample_size <- 10`

: This line creates a variable called`sample_size`

and assigns the value of 10 to it. This variable is used to specify the size of the sample we want to draw from the population.`sample(population, sample_size, replace = FALSE)`

: This is the main line that performs the sampling. The`sample()`

function is used to randomly select`sample_size`

number of elements from the`population`

vector. The third parameter,`replace = FALSE`

, means that the sample is taken without replacement, meaning that once an element is selected, it is not eligible to be selected again.

As a result, this code will output a vector of 10 random numbers from the population 1 to 100 with no repetition.

It is worth noting that the function `sample()`

uses a pseudorandom number generator. This means that it produces sequences of numbers that appear random, but are generated by a deterministic algorithm. Therefore the same seed used to initiate the generator will always produce the same sequence of random numbers.

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