Introduction to R: Exercises
6. Defining functions. You are given a vector of stock returns, which is stored as the variable returns. You want to
write a function in R to standardize the returns.
Recall that a variable can be standardized by subtracting its mean and then dividing by its standard deviation. This can be done with the functions mean() and sd().
Functions in R have the following form: function_name <- function(arg_1, arg_2, ...){classFunction body}. The last expression to be evaluated in a function is its return value.
returns <- c(1.11, 0.98, -1.01, 1.93, -3.44, -3.74, 1.21, 4.05, 1.01, 1.51, -2.27)
# Define a function to standardize a variable, X.
standardize <- ___(X) {
mean_X = mean(___)
sd_X = ___(X)
standardized_X = (___-mean_X)/___
}
# Apply the function to the stock returns data.
standardized_returns <- standardize(returns)
# Plot histogram of returns.
hist(standardized_returns)
# Define a function to standardize a variable X.
standardize <- function(X) {
mean_X = mean(X)
sd_X = sd(X)
standardized_X = (X-mean_X)/sd_X
}
# Apply the function to the stock returns data.
standardized_returns <- standardize(returns)
# Plot histogram of returns.
hist(standardized_returns)
test_error()
test_object("standardize", incorrect_msg="Did you apply the formula for standardization correctly?")
test_object("standardized_returns", incorrect_msg="Did you define `standardized_X` correctly in `standardize`?")
success_msg("Excellent work! Notice that the distribution is centered around 0.")
Did you apply the `mean()` and `sd()` functions correctly?
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