se_tests: Convenient Information About the Precision of a Random Sample

In ForestElementsR: Data Structures and Functions for Working with Forest Data

Convenient Information About the Precision of a Random Sample

Description

Given an arbitrary random sample, t-statistics are calculated in order to obtain information about the precision of the sample mean or sum. A list of useful statistics is returned, most importantly the standard error and the confidence boundaries according to the confidence level provided by the user.

Usage

se_tests(
  x,
  mu = 0,
  ref = c("mean", "sum"),
  alternative = c("two.sided", "greater", "less"),
  conf.level = 0.95
)

Arguments

x	vector representing the sample to be evaluated
mu	the hypothesized mean for the null hypothesis, standard = 0
ref	the reference value for the satistic, whether it is calculated from the mean or the sum, default = 'mean'
alternative	a character string specifying the alternative hypothesis for the t-statistics: "two-sided", "greater" or "less". Default is "two-sided"
conf.level	confidence level of the interval, Default = 0.95

Value

A list containing various statistics such as standard error, t-statistic, degrees of freedom, p-value, and confidence interval and margin of error as a percentage of the mean or sum, respectively.

Examples

set.seed(123)
data <- rnorm(100, mean = 5, sd = 2)

# Test for sum
se_tests(
  data, mu = 0, ref = "sum", alternative = "two.sided", conf.level = 0.95
)
# Test for mean
se_tests(
  data, mu = 0, ref = "mean", alternative = "two.sided", conf.level = 0.95
)

ForestElementsR documentation built on April 3, 2025, 7:47 p.m.