= Solution
\b[TODO: Complete the data-specific numerical results and diagnostics when the original `Iris_data.csv` is available.]
The estimate requested is the <sample mean>, \b[$\boxed{\bar x=n^{-1}\sum_i x_i}$]. The named electronic file `Iris_data.csv` is not present in the supplied source archive or this repository, and its measurements are not printed in the paper. Consequently its numerical <sample mean> cannot be recovered from the paper alone. The familiar built-in iris data must not be silently substituted: the question does not identify those observations as its sample.
The following R code reads the actual file and prints its <sample mean>. The later code blocks in Question 2 continue this same script and use the resulting `x`, `n` and `xbar`.
``
dat <- read.csv("Iris_data.csv", check.names = FALSE)
# Recognize common labels, or a single measurement column.
keys <- tolower(gsub("[^[:alnum:]]", "", names(dat)))
j <- which(keys %in% c("sepallength", "sepallengthcm", "x"))
if (length(j) == 0L && ncol(dat) == 1L) j <- 1L
if (length(j) != 1L) {
stop("Select the sepal-length column explicitly after inspecting names(dat).")
}
x <- dat[[j]]
stopifnot(is.numeric(x), length(x) > 0L, all(is.finite(x)))
n <- length(x)
xbar <- mean(x)
cat("n =", n, " sample mean =", format(xbar, digits = 12), "\n")
``
This reader assumes a header row and one observation per row. An alternative layout should be identified explicitly rather than dropping measurements or treating an identifier column as a length.
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