Point out the wrong statement.

A percentile is simply a quantile with expressed as a percent
There are two types of random variable
R cannot approximate quantiles for you for common distributions
None of the mentioned

The correct answer is: B. There are two types of random variable.

A percentile is simply a quantile with expressed as a percent. A quantile is a value that divides a ranked data set into two parts, so that a certain percent of the data falls below the value. For example, the 25th percentile is the value that divides the data into two parts, so that 25% of the data falls below the value.

R can approximate quantiles for you for common distributions. For example, the following code will approximate the 25th percentile of a normal distribution:

quantile(rnorm(1000), 0.25)

This will return a value that is approximately equal to the 25th percentile of a normal distribution.

There are many types of random variables, including continuous random variables, discrete random variables, and mixed random variables. A continuous random variable is a random variable that can take on any value within a given interval. A discrete random variable is a random variable that can take on only a finite number of values. A mixed random variable is a random variable that can take on both continuous and discrete values.

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