In R, you can easily calculate descriptive statistics such as mean, median, mode, standard deviation, and variance using built-in functions. Here are some examples:
## Mean
x <- c(1, 2, 3, 4, 5)
mean(x) # Output: 3
## Median
y <- c(1, 2, 3, 4, 50)
median(y) # Output: 3
## Mode
z <- c(1, 2, 2, 3, 3, 3, 4, 4, 4, 4)
Mode <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
Mode(z) # Output: 4
## Standard deviation
x <- c(1, 2, 3, 4, 5)
sd(x) # Output: 1.581139
## Variance
x <- c(1, 2, 3, 4, 5)
var(x) # Output: 2.5
In the code above, we first create vectors of numeric data for each of the statistics we want to calculate. We then use the built-in R functions to calculate the mean, median, standard deviation, and variance. For the mode, we define a custom function `Mode()` that uses the `match()` function to find the index of each unique valuein the vector, and then uses the `tabulate()` function to count the number of occurrences of each value. Finally, it returns the value with the highest count.
Note that R also has built-in functions for other descriptive statistics such as range, quartiles, and interquartile range, among others. You can find more information on these functions in the R documentation or online tutorials and resources.